Archives For philosophy of science

Author Information: Mirko Farina, King’s College London, mirko.farina@kcl.ac.uk.

Farina, Mirko. “Exploring the Concepts of Science in 166 Pages: Reviewing Nigel Sanitt.” Social Epistemology Review and Reply Collective 8, no. 4 (2019): 28-33.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-48g

A wax statue of Isaac Newton, deceased.
Image by Nadia via Flickr / Creative Commons

 

In Culture, Curiosity and Communication in Scientific Discovery, scientist Nigel Sanitt develops an empirically-informed, highly interdisciplinary, and richly holistic account of scientific progress and discovery. By drawing upon a vast range of historical and contemporary sources, Sanitt provides important, original insights to understand the nature of scientific reasoning and how it is practised.

The book contains a useful introduction in which Sanitt highlights the focal points of his project and 15 short chapters in which he further develops his positive proposal (the idea that the foundations of science are built on sand and that scientific theories are frameworks we use to model nature). The book also considers how meaning is created in science and argues that science is deeply grounded in questions.

In the first part of this critical notice I briefly summarise the book’s content. I then turn my attention to one of the most important theoretical tensions underlying it: the relationship between science and philosophy. I investigate this tension,  critically assess the claim that philosophy is dead (Hawking, 2010), and in agreement with Sanitt conclude that a synergetic relationship between science and philosophy is not only desirable but also mutually beneficial.

A Fast Walk Through Vast Territory

In chapters 1 and 2, Sanitt sets up the scene and looks at the role of truth in science (pp.2-6). He then goes on to discuss the function (prediction) of scientific theories (pp. 18-22) and their search for invariance (pp. 25-26). Sanitt also aptly reviews recent progresses in philosophy of science (pp.7-14) and convincingly argues that the foundations of science are built on sand. Let me notice here that the philosophical grounding of this latter set of ideas could have been enriched by discussing the work of Poincaré, Duhem, Lakatos and Feyerabend.

In chapters 3 and 4, Sanitt discusses two theories [the integrationist theory of meaning defended by Harris (1981); and the theory of problematology pioneered by Meyer 2014)] that play a pivotal role in the development of his book. In particular, the former (pp. 41-43) provides Sanitt with the conceptual palette for the latter, which he uses to argue that science is an answer-generating dynamic enterprise (p.53).

Chapters 5 and 6 focus on the idea that scientific theories are frameworks, networks with links and nodes (p.70), that we use to model nature. Here Sanitt gives the mathematical background to describe these networks using graph theory (pp.72-79).

Chapter 7 focuses on scientific communication and looks, in particular, at how scientists interact with the media, the public, the politicians, with scientific organisations, and with each other (pp.82-84). While the need for more public engagement is stressed, the picture that emerges is one where scientists are often forced, by lack of research funding, ‘to actively engage with all these actors in outreach, lobbying, publicity, and policy briefing’ (p.85). This highlights the political, economical and socio-cultural dimension of contemporary scientific practice, which – it is argued- may threaten the independence of science.

The central chapters of the book focus on the relation between science and literature (ch. 8), science and religion (ch. 9), science and art (ch. 10), and science and history (ch.11). Particularly interesting is chapter 10 where Sanitt looks at whether beauty (understood as Pythagorean harmony) can play a role in science (pp.105-107) and points out that many scientists were also successful artists (e.g. Feynman), musicians (e.g. Einstein, Plack, Heisenberg), or writers (e.g. Hoyle, Oppenheimer, Snow).

Chapters 12 looks at the relation between science and culture. Here Sanitt demonstrates that science -as an intellectual and practical pursuit- is deeply rooted and inexorably tied in with our culture (p.121). He also cogently argues for the crucial importance of science in our society (p.122).

Chapter 13 focuses on artificial intelligence and on consciousness (p.131).  Sanitt claims that in explaining these phenomena, ‘separating out meaning, thinking, embodiment, perception and decision making from each other does not work’ (p.135). He thus seems to endorse, albeit not stated, a view (Clark 1998) that involves mind, body and environment as direct and equal partners in the making of human cognitive behaviour.

In chapter 14 Sanitt looks at the relation between science and ethics. He reviews philosophical works on moral and ethical behaviour (pp.137-139), discusses examples of misconduct and professional malpractice in science (pp.141-142), and calls for the development of more rigorous enforcement measures to fight them (p.143).

Chapter 15 focuses on the relation between science and education, discusses gender anomalies in science (p.151) and calls for innovations (adoption of ebooks, contextualisation of textbooks) in educational practices (pp.152-153).

In chapter 16 Sanitt summarises what he has achieved in the book (pp.155-160) and concludes by condemning the idea that philosophy and science should be separated. He writes: ‘a lack of critical thinking skills leads to intellectual impoverishment and in the end, to poor science. There are many universities that include philosophy courses in their undergraduate science curriculum – this is to be encouraged’ (p.162).

Having described the contents of the monograph, I now briefly turn to what I believe is the most interesting theoretical tension underlying it; the relation between science and philosophy.

Philosophy and Science: A Sometimes Sublime Dynamic

The relation between science and philosophy is intricate and highly complicated, and is one that I can only start touching upon here. Roughly speaking we can say that until perhaps the 19th century, there was no real distinction between scientists and philosophers, and many of the greatest scientists were also great philosophers. Newton’s masterpiece, Philosophiae Naturalis Principia Mathematica (Newton, 1687/1999) is imbued with philosophical assumptions and is a paradigmatic example of this deep relation.

The gap between science and philosophy started to widen at the beginning of the last century when scientific specialisation drove a wedge between the two disciplines (Philipp, 1957). The gap became even more prominent over the last 50 years or so with the advent of the age of hyper-specialisation.

On the one hand, with the development of new technological breakthroughs, many scientists started to amass enormous amounts of empirical data (especially in disciplines like neuroscience, physics, and psychology) often forgetting (sometimes deliberately ignoring) the theoretical interpretation of such data; on the other hand, many philosophers failed to understand such developments and retreated to their ivory towers into the study of human affairs, leaving the study of nature to natural scientists and often deliberately refusing any interaction with them (this process is brilliantly summarised by Snow 1959/2012).

There were remarkable exceptions on both sides, of course. Einstein’s work (1935) demonstrated that there is a genuine interaction between science and philosophy. Heisenberg once said ‘my mind was formed by studying philosophy, Plato and that sort of thing’ (Buckley and Peat, 1996, p.6).

Russell (1914) argued that the difference between philosophy and science is of the degree not of kind.  Dewey (1938/1991) asserted that the roots of philosophy and science are the same. Poincaré (1905) and Duhem (1908/1991) spent their whole lives developing a ‘scientific philosophy’.

There are also numerous examples in the history of science that shows this deep mutual dependence and profound interaction. For example, Kepler and Sommerfeld were both inspired by Pythagorean ideas in developing their models of the harmonies of the solar system and of the atom (de Haro, 2013).

Non-Locality: Philosophy as a Guide for Quantum Physics

Next, however, I focus on the development of quantum mechanics and discuss a key moment in its history that shows how physical progress crucially depended on asking the right philosophical questions. The discussion of this case study demonstrates that the philosophical debate that took place during those years acted as a positive, driving force that pushed the development of science further.

In 1927, conflicting views on quantum physics started to crystallize. At the 5th Solvay conference in Brussels, Heisenberg declared quantum mechanics to be a ‘closed theory, whose fundamental physical and mathematical assumptions are no longer susceptible of any modification’ (Bacciagaluppi and Valentini, 2009, p. 437). With that assertion, Heisenberg voiced the feelings and the convinctions of many of his colleagues (among them Bohr, Pauli, and Dirac) also present at the conference.

Einstein, however, did not agree with Heisenberg. He believed that the so-called Copenhagen interpretation of quantum mechanics – the view that Heisenberg was indirectly defending —had philosophical implications (such as the lack of determinacy in physical quantities and events) that seemed undesirable.

Thus in 1935, with some of his colleagues (Podolsky, and Rosen), Einstein developed a famous thought experiment (known as EPR), which demonstrated the entanglement of two particles located at long distances and implied faster-than-light interactions. Since this explicitly contradicted Einstein’s theory of relativity, quantum mechanics had to be an incomplete theory and the Copenhagen interpretation had to be wrong.

With this thought experiment Einstein wanted to arrive at a theory that fullfilled some ontological desiderata. More precisely, he wanted the theory to accurately describe the real world while incorporating the requirement that physics should be independent of the observer.

While the study of paradoxes has always played an important role in physics, the formulation of the EPR paradox required the development of a neat philosophical stance about the principles and methods that were deemed to be appropriate and valuable for the development of the theory. Thus, this example paradigmatically shows that Einstein’s quest was philosophical in character and therefore that philosophical ideas indeed can play a major role in the development of scientific theories.

Contemporary Alienation

Recently, however, Stephen Hawking declared (2010) the official ‘death’ of philosophy (for similar arguments see also Weinberg, 1992 , for a review of similar arguments see Kerr, 2018). Commenting on the nature of reality, Hawking wrote: ‘traditionally these are questions for philosophy, but philosophy is dead. Philosophy has not kept up with modern developments in science, particularly physics. Scientists have become the bearers of the torch of discovery in our quest for knowledge’ (Hawking 2010, p. 5).

To be fair to Hawking, his remark seems to be about the current status of philosophy. It does not seem to be a claim about philosophy as a discipline and including all its history (as some critics of Hawking have recently argued). Also, when Hawking made that provocative claim, he probably referred to just metaphysics, the branch of philosophy that aspires to the most general understanding of nature – not to all philosophy.

Now, I don’t want to enter here the discussion of whether all metaphysics should be naturalised (Ladyman et al., 2007). But having given Hawking the fairest possible understanding, I would still like to point out that his view of contemporary philosophy is partial, misleading, and ill-informed.

This is because Hawking, when making that claim, ignored that nowadays there is lots of philosophy born out of metaphysics (philosophy of mind and cognitive science, philosophy of psychology, philosophy of neuroscience) that is deeply grounded in the sciences. He also ignored that there are many areas of research in philosophy (e.g. embodied cognition) that are inspired by scientific findings and that, in turn, guide scientific research. More importantly, he ignored that there are large groups of empirically-informed philosophers (I am one of them, for what that matters), who are increasing leaving their armchairs and ivory towers to work in close contact with scientists.

Here Sanitt, who is himself a scientist but one that is not crusading against philosophy, does (unlike Hawking) a good job in recognising the fundamental importance of philosophical thinking to scientific reasoning. He writes: ‘I believe that science research at the highest level is adversely affected by the lack of philosophical awareness and training for scientists’ (p.59).

Sanitt also recognises that ‘there are limits to the denial of philosophical import to science, which results in paralysis’ (p. 14) and goes on to condemn the process that has led to the fragmentation and alienation of science from philosophy: ‘science has been separated horizontally…from within by too much specialisation…..This separation … is also vertical in the sense that science is seen as a completely different kind of entity from areas dubbed the arts or literature. This kind of separation is just as damaging and just as specious’ (p.14).

The picture that Sanitt draws is therefore one where philosophy directly interacts with science on a number of different levels. In particular, Sanitt believes: i).that the way science is taught and practised should not be immune from philosophical speculations (p.12); ii).that philosophical theorising should play an instrumental role in raising the right questions (pp.52-55) that science aims to answer (pp.64-70); and iii).that philosophy should help scientists interfacing with the wider, non-academic, world (pp. 80-86). Sanitt sees in this collaboration the roots of scientific success and thus argues, pace Hawking, that a synergetic partnership between science and philosophy is highly desirable.

Conclusion

Culture, Curiosity and Communication in Scientific Discovery shines a light through the mist of scientific research. It convincingly makes the case that science is driven by questions that often have a philosophical nature. The book also demonstrates that the foundations of science are built on sand and that the search for truth is always elusive.

The volume is thorough and does not at all shy away from conceptual complexity – quite the opposite.  The impressive sheer wealth and breadth of information presented makes the volume worthwhile. The prose is engaging, the style is captivating, the argument is coherently presented.

Structurally, however, I question the author’s decision of having 16 short chapters, each containing a lot of different subsections (often trying to summarise complex debates in a page or two). Occasionally, this results in having half-backed subsections (e.g. ‘free will’, p.99), which do not fully capture the nuances and the complexities of the issues debated. This sometimes interrupts the flow of the argumentation and prevents the reader from understanding the main point being made.

Nevertheless, this is a much needed (and welcomed) contribution to the field. A must read for scientists and philosophers, and more generally, for all those who are interested in understanding how scientific theories are constructed and verified.

Contact details: mirko.farina@kcl.ac.uk 

References

Bacciagaluppi, Guido, and Antony Valentini. Quantum theory at the crossroads: reconsidering the 1927 Solvay conference. Cambridge, UK: Cambridge University Press, 2009.

Buckley, Paul, and F. David Peat. Glimpsing reality: Ideas in physics and the link to biology. Toronto, ON: University of Toronto Press, 1996.

Clark, Andy. Being there: Putting brain, body, and world together again. Cambridge, MA: MIT Press, 1998.

de Haro, Sebastian. “Science and Philosophy: A Love-Hate Relationship.” arXiv preprint arXiv:1307.1244 (2013).

Dewey, John. Logic, the theory of inquiry. Carbondale: IL, Southern University Press, 1938/1991.

Duhem, Pierre Maurice Marie. The aim and structure of physical theory. Vol. 13. Princeton, NJ: Princeton University Press, 1908/1991.

Einstein, Albert, Boris Podolsky, and Nathan Rosen. “Can quantum-mechanical description of physical reality be considered complete?.” Physical review 47, no. 10 (1935): 777.

Hawking, Stephen. The grand design. London, UK: Random House Digital, Inc., 2010.

Kerr, Eric. “A Hermeneutic of Non-Western Philosophy.” Social Epistemology Review and Reply Collective 7: 1-6, 2018

Ladyman, James, Don Ross, David Spurrett, and John Collier. Every thing must go: Metaphysics naturalized. Oxford, UK: Oxford University Press, 2007.

Newton, Isaac. The Principia: mathematical principles of natural philosophy. Berkeley: CA: University of California Press, 1687/1999.

Philipp, Frank. Philosophy of science: The link between science and philosophy. Englewood Cliffs, NJ: Prentice-Hall, Inc., 1957

Poincaré, Henri. Science and hypothesis. Science Press, 1905.

Russell, Bertrand. Our Knowledge of the External World as a Field for Scientific Method in Philosophy. Chicago, IL and London, UK: Open Court Publishing, 1914.

Snow, Charles Percy. The two cultures. Cambridge, UK: Cambridge University Press, 1959/2012.

Weinberg, Steven. Dream of a final theory, the scientist’s search for the ultimate laws of nature. New York, NYC: Vintage Books, (1992).

Author Information: Gregory Sandstrom, Arena Blockchain, gregory.sandstrom@gmail.com.

Sandstrom, Gregory. “Is Blockchain an ‘Evolutionary’ or ‘Revolutionary’ Technology, and So What If It Is?: Digitally Extending Satoshi Nakamoto’s Distributed Ledger Innovation.” Social Epistemology Review and Reply Collective 8, no. 3 (2019): 17-49.

The pdf of the article gives specific page references, and includes the full text of the article. Shortlink, Part One: https://wp.me/p1Bfg0-47f. Shortlink: Part Two: https://wp.me/p1Bfg0-47m

Image by Tiger Pixel via Flickr / Creative Commons

 

Ideological Blockchain Evolutionism

There is also a position held that promotes what I call ‘ideological evolutionism’ in insisting that blockchain must be called a particularly ‘evolutionary’ phenomenon. This appears to be due largely to a broader ideological framework to which the authors are already committed.

This view requires either that blockchain should not be seen as a ‘revolutionary’ technology or use ideas available in literature produced by academics that promote something akin to the ‘evolution of everything,’ i.e. that ‘everything evolves’ based on the logic that ‘everything changes.’ This ideology is professed in the works of Matt Ridley and David Sloan Wilson among others.

Patrick T. Harker, President and Chief Executive Officer for the Federal Reserve Bank of Philadelphia, tells us that, “banking evolved its products and appendages just like the first single-cell organisms evolved fins and gills and eventually feet and legs.” (2017: 4) Here an analogy with the origins of life and animals implies that blockchain is an innovation of almost mythical proportion. Though it may surprise the people who use ‘evolution’ colloquially to hear this, not a few people actually do link the rise of blockchain to a broader understanding of life, human existence and their general worldview.

One of the most well-known ideological blockchain evolutionists is Naval Ravikant, co-founder of Angel List. “The Evolution of Everything by Matt Ridley, one of my favorite authors,” tells Ravikant. “If I can’t verify it on my own or if I cannot get there through science, then it may be true, it may be false, but it’s not falsifiable so I cannot view it as a fundamental truth. On the other side, I do know that evolution is true. I do know that we are evolved as survival and replication machines. I do know that we have an ego so that we get up off the ground and worms don’t eat us and we actually take action.” Ravikant also appeared on a podcast with Tim Ferris using a title “The Evolutionary Angel[1].” In short, Ravikant says, “I think almost everything about humans and human civilization is explained better by evolution than anything else[2].” To clarify what he means, he says,

“I use evolution as my binding principle in that it can explain a lot about how we behave towards each other and why we do certain things. / Ignoring that your genes want you to live in a certain way is a delusion that is going to hurt you. / I think a lot of modern society can be explained through evolution. One theory is that civilization exists to answer the question of who gets to mate. If you look around, from a purely sexual selection perspective, sperm is abundant and eggs are scarce. It’s an allocation problem. How do you choose which sperm gets the egg? / Literally all of the works of mankind and womankind can be traced down to people trying to solve that problem.”[3]

In short, we see an attempt at the ‘naturalisation’ of blockchain technology based on ideology or worldview, rather than ‘science.’

Similarly, but with a more academic focus, Chris Berg et al. (2018) are promoting an institutional evolutionary approach that mixes together ‘development’ with ‘evolution’. They ask: “How do blockchain protocols develop? How do they evolve? It is useful to see the development of blockchain innovation through the entrepreneurial innovation literature. Each sequential adaptation of a blockchain represents a new economic organisation, such as a firm.” (Ibid: 3)

For them, “Blockchain protocols offer us an evolutionary window into institutional change. The protocols are evolving under variation, replication and selection conditions, and researchers have a near complete and comprehensive window into those changes.” (Ibid: 10) This choice of terms follows on the work of Donald T. Campbell who attempted to apply Darwinian principles regarding biology to the human world, using the controversial notion of ‘blind variation and selective retention’ (cf. the Darwinian notion of ‘random mutation and natural selection’), which at the same time dislocates humanity’s power of choice by removing the teleological impulse[4] that is present in non-evolutionary and trans-evolutionary (Sandstrom 2016) viewpoints.

Nick Szabo is a major figure in blockchain space, perhaps most known for his coinage of the term ‘smart contract.’ Szabo is also somewhat prolific in his use of the term ‘evolution’ when it comes to cultural artefacts. He writes, “Common law is a highly evolved system of security for persons and property.” This draws on his general belief that, “Over many centuries of cultural evolution has emerged both the concept of contract and principles related to it, encoded into common law. Algorithmic information theory suggests that such evolved structures are often prohibitively costly to recompute. If we started from scratch, using reason and experience, it could take many centuries to redevelop sophisticated ideas like property rights that make the modern free market work.”

Szabo, however, notes that, “the digital revolution is radically changing the kinds of relationships we can have. … New institutions, and new ways to formalize the relationships that make up these institutions, are now made possible by the digital revolution. I call these new contracts ‘smart,’ because they are far more functional than their inanimate paper-based ancestors.” (1996) At the same time, he reminds us that, “Societies have evolved institutions such as firms and competitive markets to set prices, legal precedents and judicial proceedings to make judgments, and so forth.” (2002) Thus, we are proposed with a digital revolution happening inside of a broadly evolutionary version of human history.

Kartik Hegadekatti (2017) believes that, “Man has not only evolved biologically and culturally but also economically. Human economy has grown over many centuries through continuous addition of value. This value addition has been an evolutionary factor as it has influenced the formation of the main economic sectors-namely Primary, Secondary and Tertiary. Recently after the advent of Blockchain technology, Bitcoin achieved Gold parity. This paper analyses whether such an event will have any impact on the evolution of our economies.”

He suggests that,

“Man first settled down for agriculture, and started the process of economic and social development. In fact, this event led to conditions where mankind could experiment and evolve new economic and social systems. Earlier, during the hunter-gatherer phase, there were very few niche specialties. A hunter had to sharpen his [sic] own spear and go to hunt with the group. Once man settled down, distribution and differentiation of labor started. Villages sprang up where there were blacksmiths, cattle herders, and traders etc. who became part of the then-nascent human society.” (2017: 3)

Further, he writes that, “Consequently we may witness an explosion in technology entities, akin to the industrial revolution; A Technology Revolution. This may culminate in the creation of a truly Artificial Intelligence (as investment and research into Data analytics and automation technology will increase, thanks to investment in Blockchain Technology) leading to Technological Singularity.” (Ibid: 6)

In this final example of ideological blockchain evolutionism, we notice the author predicting a ‘Technological Singularity’ (cf. Ray Kurzweil’s dystopian scenario for humanity), which presents a kind of teleological goal and aim for human-machine interaction. Proponents of blockchain development who share this view may thus somehow still believe in technological revolutions that happen within a broader worldview in which everything, inevitably, is always and everywhere evolving.

Digitally Extending Blockchain

“The idea of cultural evolution strikes me as nothing but a dodge to put off the work of doing th[e] thinking, a piece of displacement activity brought in to dodge the conflict. It is not the right way to grasp the continuity between human and non-human nature. We need to drop it and find a better path[5].” – Mary Midgley (1984)

“Practitioners should be skeptical of claims of revolutionary technology.”

– Arvind Naryanan and Jeremy Clark (2017)

After having considered the ways various people write about blockchain as a constantly changing and ‘evolving’ technology, potentially a ‘revolutionary’ one, in this section I will offer an additional approach to blockchain development. My view is that blockchain technology is an example of a ‘social machine[6]‘ (Berners-Lee 1999) that most closely resembles the educational and agricultural extension movements from the late 19th and 20th centuries, which continue around the world today.

It is not necessary and can even be harmful or at least restrictive to use ‘evolutionary’ language to describe this alternative approach. In the current 21st century, we can thus consider the emergence and development of blockchain as a form of ‘digital extension services,’ which I will briefly elaborate on below and further in a forthcoming book chapter (Bailetti IGI, 2019).

The first thing to realise in order to make a simple yet crucial shift in language is that ‘change’ is the master category, not ‘evolution’ or ‘revolution’. That is to say that both evolution and revolution require change to happen, but change need not be either evolutionary or revolutionary. That is what makes change the master category over both evolution and revolution.

This basic semantic point serves an aim to help curb the rampant over-use and exaggeration of the ‘biological theory of evolution’ into the field of technology development that at the same time largely avoids identifying non-evolutionary or trans-evolutionary (Sandstrom 2017c) types of change. Instead, properly identifying the master category reveals that the intended new directions of social and cultural change due to blockchains are happening less rapidly and possibly also less disruptively compared to what many ‘blockchain revolution’ proponents enthusiastically claim.

Here it is worth noting that blockchain technology is based on not a few prior innovations, which when taken into account make it appear less revolutionary and more step-wise logically sequential. Such is the case that Naryanan and Clark make in their impressive paper “Bitcoin’s Academic Pedigree (2017). In it they state that, “many proposed applications of blockchains, especially in banking, don’t use Nakamoto consensus. Rather, they use the ledger data structure and Byzantine agreement, which, as shown, date to the ’90s. This belies the claim that blockchains are a new and revolutionary technology.” (Ibid)

They continue, concluding that, “most of the ideas in bitcoin that have generated excitement in the enterprise, such as distributed ledgers and Byzantine agreement, actually date back 20 years or more. Recognize that your problem may not require any breakthroughs—there may be long-forgotten solutions in research papers.” (Ibid) While nevertheless celebrating the significant achievement that Satoshi Nakamoto made in bringing multiple previous innovations together into Bitcoin, Naryanan and Clark reveal how the ‘revolutionary’ language of some proponents of blockchain can be considered as an exaggeration that avoids its historical precursors and likewise neglects the ‘shoulders of giants’ on which Nakamoto stood.

Junking the Blockchain Hype

Instead of either ‘evolution’ or ‘revolution,’ the alternative term ‘extension’ identifies inherently teleological, intentional and goal-oriented change-over-time. This term also adds considerable untapped value in connecting directly with the history of educational extension and agricultural extension mentioned in the introduction.

In both cases, the extension of knowledge, training and scientific innovations from centres to margins and from people in cities and at research institutes to people in rural areas around the world without convenient access to educational institutions has opened new opportunities for social learning and overall human development[7].

Thus, blockchain framed as an example of ‘digital extension services’ provides an analogy with applications for business, finance, governance[8], military[9], education, agriculture[10], cultural heritage[11], and any and all other institutions in society that may make use of peer-to-peer transaction-based systems that can be measured with data collection.

Burton Swanson et al. define ‘extension’ as “the organized exchange of information and the purposive transfer of skills.” (1997) It was such intentional diffusion of creative innovation and knowledge sharing that led to a worldwide movement of ‘extensionsists’ and ‘extension agents,’ that has arguably become the greatest social impact force, both personally and institutionally, perhaps alongside of universities, football (soccer) and major religions, that the world has ever known and experienced.

This is why I believe a discussion now of blockchain as ‘digital extension services’ is particularly ripe for exploration and why the regularly repeated question of whether or not blockchain is an ‘evolution or revolution’ is not currently as important. If blockchain is going to become a ‘revolutionary’ technology in the digital era, an ‘internet of trust,’ then it will require require some kind of individual and social ‘extension’ motif with goals, aims and purposes in mind in order to achieve this.

At the same time it appears crucial, however, to openly reject ‘evolutionary’ approaches to blockchain as if believing that the origin of Bitcoin did not happen as the result of a random and undirected process that was simply a result of external ‘environmental pressures’ (cf. blind variation and selective retention). Rather, Bitcoin and the technology now known as ‘blockchain’ were created intentionally by a pseudonymous programmer and cryptographer in 2008, with the first Bitcoin mined on January 3, 2009.

If Satoshi Nakamoto’s intentional creation is not credited as such, then an invitation to future blockchain chaos without planning or purpose will be the likely result. In short, an ‘evolutionary’ origins story for blockchain falls short of validity and simply makes no logical sense. Instead, more goal-oriented and teleological discussion is needed about where we are now heading through the use of distributed ledgers, which indeed may bring highly transformative social change to people around the world through digital peer-to-peer interactions.

Investment in Revolution

The question of whether or not blockchain is potentially a ‘revolutionary’ technology and what impact it will have on society raises many difficult questions to answer. To some degree it must involve speculative futuristics. The promises of ‘decentralisation’ and the removal of intermediaries (disintermediation) from digital social transactions that happen across borders and nations using the internet has led to what can be called ‘centre-phobia,’ or the fear of centralised institutions of social, economic and political power. Some proponents of blockchain are even calling for ‘leaderless democracy[12],’ which sounds more utopian and radical than what mainstream blockchain builders are aiming for.

The blockchain feature of having a timestamped, immutable record has many implications, including for deterrence of online criminal activity and financial fraud detection[13]. While much of the zeal for Bitcoin in the early years involved illicit use through the Silk Road website involving weapons, drugs, human trafficking and various nefarious schemes, other non-criminal uses of distributed ledger for ‘social impact[14]‘ soon started to arise that pushed the boundaries of what peer-to-peer networking and transacting around the world could enable.

All of these changes require the intentional and ‘signed’ (cf. key signatures) use of blockchain systems, where users must agree to accept the rules and regulations of the ledger community’s ‘Genesis Block’ in order to participate. Again, the language of ‘extension’ based on individual and social choices seems more suitable than outsourcing the conversation to biological or even environmental language.

To enable easily distinguishing ‘non-evolutionary’ change and ‘development’ from ‘evolutionary’ change, we may simply consider the effects of intentionality, purpose and aim[15]. When we explore the directions and trajectories that blockchain DLT is headed, we mean that people are consciously developing and building it and/or purchasing crypto-assets and digital currencies, i.e. they are ‘extending’ the innovation made by Satoshi Nakamoto with new applications.

Rest assured, however, with this new terminology in hand this does not necessarily mean that any one person knows, or even that it can be known exactly for certain, in which direction(s) blockchain is headed, such that a single person, group or institution can ‘control’ it, as Carter rightly identified above. Yet, while most people cautiously say they do not now know and cannot predict where blockchain is headed in the future, those who are actually building blockchains now should properly be given credit for their work and not left out of the conversation as if their plans are irrelevant to the eventual outcome of the technology’s growth.

Indeed, the goals, aims, visions and plans of many blockchain builders and investors will determine the trajectory of blockchain development; they are the ones who are now ‘in control’ of where the technology is headed since Satoshi Nakamoto has disappeared from public[16].

Similarly, the perspective which holds that all change that is gradual, rather than rapid, therefore, according to biological precedent, automatically counts as ‘evolutionary,’ turns out to be both false and unnecessary upon closer investigation. French Nobel prize winner in Medicine, François Jacob suggested that, “Natural selection does not work as an engineer works. It works like a tinkerer — a tinkerer who does not know exactly what he is going to produce but uses whatever he finds around him… to produce some kind of workable object[17].”

Yet with blockchain the ‘human selection[18]‘ or ‘human extension’ of technology is being done by software developers, legal experts and innovation leaders with particular practical goals and business solutions in mind, even if ‘tinkering’ is the method by which the development occurs. The key is that people are actively involved in plotting the trajectory of blockchain growth and application, in contra-distinction with the mere anthropomorphic appearance (design) of biological change over time.

It simply does not make sense, therefore, when speaking about blockchain technology to use the language of a biologist like Dawkins, who suggested based largely upon a reactionary view, that ‘natural selection,’ “has no purpose in mind. It has no mind and no mind’s eye. It does not plan for the future. It has no vision, no foresight, no sight at all. If it can be said to play the role of watchmaker in nature, it is the blind watchmaker.” (1986: 5) Instead, with blockchain, it is our deep sense of purpose, vision, foresight, and planning that will result in new opportunities to apply the technology in potentially beneficial and effective social and cultural, economic and political configurations.

Indeed, the all-too-human sense of vision and deliberate drive, even if the direction was not always entirely clear and involved a kind of groping for solutions towards an unknown future; this is what enabled Satoshi Nakamoto to bring together past innovations, to ideate, code and eventually build a technological, legal framework and community for Bitcoin users in the first place.

To write this off according to a non-inventive theory of biological evolution that has no foresight or personal agency is to unnecessarily reduce and even dangerously dehumanise the conversation about blockchain in a disparaging way. Instead, I believe that aiming to uplift the conversation involving blockchain for humanity’s individual and collective extension and benefit is what the situation now most urgently requires.

What was the problem to which blockchain presented a solution? Was Nakamoto mainly aiming to undermine the power of financial institutions following the USA’s Emergency Economic Stabilization Act of 2008, i.e. the great bailout for banking elites at massive cost to millions of citizens? What purposes need there be other than financial ones to inspire the invention of an immutable public ledger that may serve as the basis for a ‘blockchain revolution’?

A public ledger (cf. triple entry accounting) that eliminates the double spending problem for digital transactions involving money is a massively transformative technology in and of itself. Regardless of what purposes Nakamoto had in mind when designing, creating and developing Bitcoin, we now are faced with what to do with this invention in ways that not only disrupt older systems, but that rather may at the same time creatively uplift human development of people around the world. What seems most urgently needed nowadays is a globally-oriented, socially-responsible digital extension services built upon distributed ledger technologies, using a combination of human, informational and material resources to produce it.

Conclusion

“The extensions of man with their ensuing environments, it’s now fairly clear, are the principal area of manifestation of the evolutionary process[19].” – McLuhan (1968)

“Building is the only truth path. Creation.” … “Bitcoin started because of my ideas. It was my design, and it is my creation.” – Craig Steven Wright (2019)

Given the above survey of uses of both terms ‘evolution’ and ‘revolution’ with respect to blockchain in the available literature, it is clear at least that there is on-going debate between which term is more suitable. My preference is to drop the term ‘evolution’ as unnecessarily ambiguous and imprecise when applied to technology, while cautioning that ateleological language is not particularly helpful or constructive in the conversation about blockchain development.

Likewise, at this early stage of historical growth, we still don’t know what kind of ‘revolution’ blockchain may cause in combination with other emerging digital technologies (IoTs, UAVs, VR/AR, virtual assistants, neural nets, quantum computing, etc.). We may thus look with either some trepidation or tempered optimism at the potential for revolutionary changes with the coming of distributed ledgers, particularly in the way blockchain will impact society, economics, politics, and culture.

In this paper, a brief comparison towards blockchain’s ‘revolutionary’ impact was proposed in the educational extension movement and agricultural extension and advisory services. The worldwide extension movement in agriculture contributed to the so-called ‘Green Revolution[20]‘ of the 1950s and 60s through knowledge sharing and information transfer to farmers who otherwise would not have had access to new seeds, knowledge and farming techniques.

With blockchain as a globally-oriented technology built upon the internet, we are starting to see new opportunities for digital identity provision that opens access to vital resources for those who are currently identity-less, for money transfer across borders (remissions), and for opportunities to bring ‘banking to the unbanked.’ This transformation has the potential to unlock many available human resources that will be able to further develop societies and cultures through savings and investment in peoples’ futures, something now impossible via institutional gridlock, exclusion and information capture.

On the strictly academic level, distributed ledgers may turn out to be the greatest technology created since the ‘social survey’ (or questionnaire) itself with the prospect of gathering big data for multivariate analysis. Now with a partially anonymous (cf. pseudonymous) user platform to protect personal identities from recrimination and ‘outing,’ social scientific research may be able to provide greater safety and security for ethical studies of humanity via digital devices that was simply not available in the past.

Nevertheless, we are still largely in the theoretical stage of blockchain’s coming impact and no mass platform for collecting such linked social data has yet been created where peer-to-peer interactions can produce a cascading global network effect. The question of whether a ‘revolution’ is coming or not due to blockchain DLT is thus for many people one still of sheer fantasy or hopeful speculation waiting for a major consensus-building breakthrough.

The Origins and the Future

Whether or not a person believes Craig Steven Wright was ‘Satoshi Nakamoto’ (perhaps with helpers alongside) or not is beside the point that someone must have been the inventive creator of Bitcoin. It simply didn’t arise on its own without an inventor and creator or without a purpose, aim and plan for its roll-out. To posit an ‘evolutionary origin’ for blockchain DLT thus profoundly misses out on the crucial elements of intentional, planned, purposeful technological change. Instead, looking at blockchain as an ‘extension’ of peoples’ choices places priorities on human values and desires, which are not to be ignored, but rather individually and collectively celebrated.

That said, in closing it is worth noting that a ‘revolution’ would only happen involving blockchains if the technology is not limited in usage to banks, multi-national corporations, and intermediary holders of financial power that collect fees without adding actual value to communities and users. Rent-seeking behaviour and currency speculation indeed has levied a massive cost on human civilisation in terms of widening the inequality gap within and between nations.

Similarly, writes Lawrie, “the Extension Movement … had to battle against the prejudice of those who would prefer university education to remain a privilege for the few.” (2014: 79) An overall struggle for power can and therefore must be expected in attempts to control distributed ledgers via ‘super users’ and centralised databases that sell user information. If the champions of blockchain DLTs are also champions of human freedom and dignity of person, the result may turn out better for a majority, rather than a minority few.

The dangers also adds caution and concern to those who focus on blockchain’s supposed ‘revolutionary’ impact as something necessarily disruptive and even destructive. The rhetoric heats up especially when blockchain is framed as a kind of deterministic, unavoidable and inevitable change driven by forces outside of human control.

Does technology have a ‘mind of its own?’ If not, then who is in control? Who is innovating? Who is guiding, choosing and directing the development of blockchain technology? And are they creating it for their own selfish gains or for the broader aims of society and culture? These questions animate the underlying concerns in this paper that mainly attempted to distinguish between random, unguided and guided, responsible technological change.

While it is true that in some sense the identity of Satoshi Nakamoto does not matter anymore, as the so-called “genie is out of the bottle[21]” now with blockchain. I believe it is nevertheless wrong to suggest that no one is or even should be in control of blockchain development, even though Satoshi Nakamoto disappeared. The growing number of people now building blockchain technologies will create a new horizon in which this technology will impact humanity in the coming years in a profound way. We may therefore watch with interest at the various ways P2P and E2E digital interactions on a global scale will change the course of human history in the near future to come.

In short, blockchain technology is a non-evolutionary or trans-evolutionary phenomenon that is potentially revolutionary for how it will restructure human society and culture based on immutable, timestamped distributed public ledgers. Blockchain as a ‘social machine’ heralds digital extension services and a new era of social change-over-time. Let us be ready and unafraid to face the challenges that this technology brings as it both disrupts, re-creates and unites people in a way that was unimaginable until Satoshi’s blockchain was invented to change the world.

Contact details: gregory.sandstrom@gmail.com

References

Arner, D.W., J.N. Barberis, R.P. Buckley (2015) “The Evolution of FinTech: A New Post-Crisis Paradigm.” 47 Geo. J. Int’l L. 1271.

Antonopolous, Andreas M. (2017). Mastering Bitcoin Programming the Open Blockchain. 2nd Edition, O’Reily.

Ashley, Michael (2019). “Forget Darwinian Evolution. Humanity May Soon Evolve Itself Through A.I.” Forbes. https://www.forbes.com/sites/cognitiveworld/2019/01/15/forget-darwinian-evolution-humanity-may-soon-evolve-itself-through-a-i/

Matthew Bardeen and Narciso Cerpa (2015). “Technological Evolution in Society – The Evolution of Mobile Devices.” https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762015000100001

Bejan, A., J.D. Charles, and S. Lorente (2014). “The Evolution of Airplanes.¨ Journal of Applied Physics, 116:044901.

Belady, L.A. And M.M. Lehman (1976). “A Model of Large Program Development.” IBM Systems Journal, 15(3): pp. 225-252.

Berg, Chris, Sinclair Davidson, and Jason Potts (2018). “Institutional Discovery and Competition in the Evolution of Blockchain Technology.” SSRN.

Berners-Lee, Tim (2000). Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web. New York: Harper.

Blakstad S., Allen R. (2018). “Ecosystem vs Egosystem and Revolution vs Evolution.” In: FinTech Revolution. Palgrave Macmillan, Cham.

Brooks, Fred P. (1986). “No Silver Bullet — Essence and Accident in Software Engineering.” Proceedings of the IFIP Tenth World Computing Conference: pp. 1069–1076.

Brooks, Fred (1975). The Mythical Man-Month. Addison-Wesley.

Brey, Phillip (2008). ‘Technological Design as an Evolutionary Process.” In Philosophy and Design: From Engineering to Architecture. Eds. P. Vermaas, P. Kroes, A. Light and S. Moore,  Springer.

Buitenhek, Mark (2016). “Understanding and applying Blockchain technology in banking: Evolution or revolution?” Journal of Digital Banking, Volume 1 / Number 2 / AUTUMN/FALL 2016, pp. 111-119 (9).

Campbell, Donald T. (1960). “Blind Variation and Selective Retention in Creative Thought as in other Knowledge Processes.” Psychological Review, 67: pp. 380-400.

Casey, M.J., P. Vigna (2015). “Bitcoin and the Digital-Currency Revolution.” Wall St. J.23. https://www.wsj.com/articles/the-revolutionarypower-of-digital-currency-1422035061

Chakraborty, Sumit (2018). FinTech: Evolution or Revolution. 1st Edition.

Champagne, Phil (2014). The Book of Satoshi: The Collected Writings of Bitcoin Creator Satoshi Nakamoto. E53 Publishing.

Dawkins, Richard (1986). The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe without Design. Norton & Company.

De Breuck, Frederik (2019). “Next steps in the evolution of blockchain.” https://blog.global.fujitsu.com/next-steps-in-the-evolution-of-blockchain/

Demirbas, Ugur, Heiko Gewald, Bernhard Moos  (2018). “The Impact of Digital Transformation on Sourcing Strategies in the Financial Services Sector: Evolution or Revolution?”  Twenty-forth Americas Conference on Information Systems, New Orleans.

Dhaliwal, Jagjit (2018). “The Evolution of Blockchain.” https://www.linkedin.com/pulse/evolution-blockchain-jagjit-dhaliwal-pmp/

Douthit, Chris (2018) “The Evolution of BlockchainWhere Are We?” https://hackernoon.com/the-evolution-of-blockchain-where-are-we-f0043b2d0cd0

Easley, David, Maureen O’Hara, and Soumya Basu (2017). “From Mining to Markets: The Evolution of Bitcoin Transaction Fees.” SSRN.

ElBahrawy, A., L. Alessandretti, A. Kandler, R. Pastor-Satorras, & A. Baronchelli (2017). “Evolutionary dynamics of the cryptocurrency market.” Royal Society Open Science, 4(11), 170623.

Fenwick, M., W.A. Kaal, EPM Vermeulen (2017). “Legal Education in the Blockchain Revolution.” 20 Vand. J. Ent. & Tech. L. 351.

Gilder, George (2018).  Life after Google: the Fall of Big Data and the Rise of the Blockchain Economy. Gateway Editions.

Harker, Patrick T. (2017). “FinTech: Evolution or Revolution?” Technology, Business and Government Distinguished Lecture Series.

Halaburda, Hanna (2018). Blockchain Revolution Without the Blockchain. Bank of Canada.  

Hedera Hashgraph Team (2018). “The Evolution of Possibilities.” https://www.hedera.com/blog/the-evolution-of-possibilities

Hegadekatti, Kartik (2017). “Blockchain Technology – An Instrument of Economic Evolution?” SSRN. https://mpra.ub.uni-muenchen.de/82852/

Herraiz, Israel, Daniel Rodriguez, Gregorio Robles, Jesus M. Gonzalez-Barahona (2013). “The Evolution of the Laws of Software Evolution”. ACM Computing Surveys. 46 (2): pp. 1–28.

Hochstein, Mark (2015). “BankThink: Fintech (the Word, That Is) Evolves.” https://www.americanbanker.com/opinion/fintech-the-word-that-is-evolves

Kakavand, Hossein, Nicolette Kost De Sevres and Bart Chilton (2017). “The Blockchain Revolution: An Analysis of Regulation and Technology Related to Distributed Ledger Technologies.” SSRN.

Künnapas K. (2016). “From Bitcoin to Smart Contracts: Legal Revolution or Evolution from the Perspective of de lege ferenda?” In: Kerikmäe T., Rull A. (eds) The Future of Law and eTechnologies. Springer, Cham .

Lagarde, Christine (2018). “Winds of Change: The Case for New Digital Currency.” https://www.imf.org/en/News/Articles/2018/11/13/sp111418-winds-of-change-the-case-for-new-digital-currency

Lawrie, Alexandra (2014). The Beginnings of University English Extramural Study, 1885– 1910. Palgrave Macmillan.

Lehman, Meir M. (1980). “Programs, Life Cycles, and Laws of Software Evolution”. Proc. IEEE. 68 (9): pp. 1060–1076.

Liu, Stella (2017). “Green Revolution 2.0 aims to boost rural net connectivity.” https://www.nst.com.my/opinion/columnists/2017/07/254923/green-revolution-20-aims-boost-rural-net-connectivity

Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system.

Narayanan, Arvind and Jeremy Clark (2017). “Bitcoin’s Academic Pedigree.” Communications of the ACM, 60, 12: pp. 36-45.

Naryanyan, V. (2018). A brief history in the evolution of blockchain technology platforms.” https://hackernoon.com/a-brief-history-in-the-evolution-of-blockchain-technology-platforms-1bb2bad8960a

Nichols, Megan Ray (2018). “Blockchain: The Next Big Disruptor in the Manufacturing Industry.” https://news.thomasnet.com/featured/blockchain-the-next-big-disruptor-in-the-manufacturing-industry/

Pinna, Andrea and Wiebe Ruttenberg (2016). “Distributed Ledger Technologies in Securities Post-Trading Revolution or Evolution?” ECB Occasional Paper No. 172.

Rauchs, Michel, Andrew Glidden, Brian Gordon, Gina Pieters, Martino Recanatini, François Rostand, Kathryn Vagneur and Bryan Zhang (2018). Distributed Ledger Technology Systems: A Conceptual Framework. Cambridge Centre for Alternative Finance.

Ravikant, Naval (2017). “The Knowledge Project.” The Farnam Street Learning Company. https://fs.blog/wp-content/uploads/2017/02/Naval-Ravikant-TKP.pdf

Rose, C. (2015). “The Evolution Of Digital Currencies: Bitcoin, A Cryptocurrency Causing A Monetary Revolution.” International Business & Economics Research Journal (IBER), 14(4): pp. 617-622.

Sahlstrom, Dennis (2018). “The Future is Here – The Evolution of Blockchain.” https://toshitimes.com/the-future-is-here-the-evolution-of-blockchain/

Sandstrom, Gregory (2017). “Anyone Who Thinks Blockchain Technology is Evolving Put Your Hand Up.” https://medium.com/@gregory.sandstrom/anyone-who-thinks-blockchain-technology-is-evolving-put-your-hand-up-a80c30644894

Sandstrom, Gregory (2017a). “Enter Blockchain: The Non-Evolutionary Recovery of Genesis  in Contemporary Discussions of Innovation and Emerging Technologies.” https://medium.com/@gregory.sandstrom/enter-blockchain-the-non-evolutionary-recovery-of-genesis-in-contemporary-discussions-of-96ae135413a6

Sandstrom, Gregory (2017b). “Who Would Live in a Blockchain Society? The Rise of Cryptographically-Enabled Ledger Communities.” Social Epistemology Review and Reply Collective 6, no. 5: pp. 27-41. https://social-epistemology.com/2017/05/17/who-would-live-in-a-blockchain-society-the-rise-of-cryptographically-enabled-ledger-communities-gregory-sandstrom/

Sandstrom, Gregory (2017c). “Evolutionary Epistemology.” Wiley-Blackwell Encyclopedia of Social Theory.

Sandstrom, Gregory (2016). “Trans-Evolutionary Change Even Darwin Would Accept.” Social Epistemology Review and Reply Collective 5, no. 11, 2016: pp. 18-26.

Sandstrom, Gregory (2010). “The Extension of ‘Extension’ OR the ‘Evolution’ of Science and Technology as a Global Phenomenon.” Liberalizing Research in Science and Technology: Studies in Science Policy. Eds. Nadia Asheulova, Binay Kumar Pattnaik, Eduard Kolchinsky, Gregory Sandstrom. St. Petersburg:  Politechnika: pp. 629-655.

Sandstrom, Gregory (2010). “The Problem of Evolution: Natural-Physical or Human Social?” In Charles Darwin and Modern Biology. St. Petersburg: Institute for the History of Science and Technology, Russian Academy of Sciences: pp. 740-748.

Sinrod, Margaret Leigh (2018).  “Still don’t understand the blockchain? This explainer will help.” https://www.weforum.org/agenda/2018/03/blockchain-bitcoin-explainer-shiller-roubini

Smart, Paul R. (2012). “The Web-Extended Mind.” In Special Issue: Philosophy of the Web, Metaphilosophy, 43, (4): pp. 426-445.

Smart, P.R., & Shadbolt, N.R. (2015). “Social Machines.” In Encyclopedia of Information Science and Technology, Third Edition. IGI Global: pp. 6855-6862.

Staples, M., S. Chen, S. Falamaki, A. Ponomarev, P. Rimba, A.B. Tran, I. Weber, X. Xu, L. Zhu (2017). “Risks and Opportunities for Systems Using Blockchain and Smart Contracts.” Data61 (CSIRO).

Swan, Melanie (2015). Blockchain: Blueprint for a New Economy. Sebastopol: CA: O’Reilly.

Swanson, Burton E., Robert P. Bentz and Andrew J. Sofranko (1997). Improving Agricultural Extension: A Reference Manual. Rome: Food and Agriculture Organisation of the United Nations. http://www.fao.org/docrep/w5830e/w5830e00.htm

Szabo, Nick (2002). “Measuring Value.” http://www.fon.hum.uva.nl/rob/Courses/InformationInSpeech/CDROM/Literature/LOTwinterschool2006/szabo.best.vwh.net/measuringvalue.html

Szabo, Nick (1996). “Smart Contracts: Building Blocks for Digital Markets.” http://www.fon.hum.uva.nl/rob/Courses/InformationInSpeech/CDROM/Literature/LOTwinterschool2006/szabo.best.vwh.net/smart_contracts_2.html

Tapscott, Don & Alex (2016). The Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World. Portfolio Penguin.

Town, Sam (2018). “Beyond the ICO Part 3: Evolution Versus Revolution.” https://cryptoslate.com/beyond-the-ico-part-3-evolution-versus-revolution/

Trujillo, Jesus Leal, Stephen Fromhart & Val Srinivas (2017). “Evolution of blockchain technology Insights from the GitHub platform.” Deloitte.

Walport, Mark (2016). “Distributed Ledger Technology: beyond block chain. A report by the UK Government Chief Scientific Adviser.”

Williams, Sam (2002). “A Unified Theory of Software Evolution.” Salon.

Wright, Collin (2018). “The New Evolution Deniers.” https://quillette.com/2018/11/30/the-new-evolution-deniers/

Wright, Craig Steven (2019). “Careful what you wish for…” https://medium.com/@craig_10243/careful-what-you-wish-for-c7c2f19e6c4f

Wright, Craig Steven (2019a). https://medium.com/@craig_10243/proof-of-work-1a323e82fd9

Videos

“Alex Tapscott: Blockchain Revolution | Talks at Google” – https://www.youtube.com/watch?v=3PdO7zVqOwc

“Are Blockchains Alive? Co-evolving with Technology” – Amanda Gutterman (ConsenSys) – https://www.youtube.com/watch?v=X7GkkGTnVwA

“Block Chain Revolution | Giovanna Fessenden | TEDxBerkshires” – https://www.youtube.com/watch?v=oMhZTEQZJPI

“Bitcoin and the history of money” – “Let’s take a look at the evolution of money.” – https://www.youtube.com/watch?v=IP0jCjyrew8

“Blockchain – evolution or revolution?” –  https://www.youtube.com/watch?v=LojzPukAtmM

“Blockchain Evolution & Empowerment” – https://www.youtube.com/watch?v=eSUC9NFccNk

“Blockchain Evolution 2” – Reese Jones – https://www.youtube.com/watch?v=mCPqXHt-z0k

“Blockchain Evolution or Revolution in the Luxembourg Financial Place? – Nicolas Carey https://www.youtube.com/watch?v=Wp9FB_JQlgI

“Blockchain Evolution” – https://www.youtube.com/watch?v=CULUqgfVteg

“Blockchain Evolution” – Complexity Labs – https://www.youtube.com/watch?v=rO2LSBDekvE

“Blockchains’ Evolution by natural selection like biology’s genetics” – Reese Jones – https://www.youtube.com/watch?v=4JEFGtsu0s4

“Blockchain Evolution” – https://www.youtube.com/watch?v=tGcuJoFZLOY

“Chandler Guo on The Bitcoin & Blockchain Revolution” – https://www.youtube.com/watch?v=J7g2JFn68LU

“Cryptos Are The EVOLUTION of Money and Blockchain is the REVOLUTION of Trust! Vlog#18” – Siam Kidd – https://www.youtube.com/watch?v=-nu2F6_K0S0

“DigiByte Blockchain – The evolution of the Internet & the revolution in the financial systems” – https://www.youtube.com/watch?v=w8h10ckU0sE “The revolution has already begun.”

“Don Tapscott – The Blockchain Revolution – https://www.youtube.com/watch?v=gZEmaSbqfYQ

“Evolution of Bitcoin” – Documentary Film – https://www.youtube.com/watch?v=HUpGHOLkoXs

“Evolution of Blockchain And Its Future Moving Forward In 2018!” – https://www.youtube.com/watch?v=YWlMoxMTbDQ

“Evolution of Blockchain in India:The value of Ownership.” – Mr.Akash Gaurav – TEDxKIITUniversity – https://www.youtube.com/watch?v=BtTJmb0jYzE

“Evolution of the Blockchain Economy” – Jeremy Gardner – Startup Grind – https://www.youtube.com/watch?v=Q7cPy6ITUm4

“Future Evolution of Blockchain” – Silicon Valley TV – https://www.youtube.com/watch?v=5_6m7LYIEo4

“Future Thinkers Podcast – a podcast about evolving technology, society and consciousness. https://futurethinkers.org/

“Genetics of Blockchain Evolution” – Reese Jones – https://www.youtube.com/watch?v=8fFsmuvyXeE

“Keynote: Blockchain’s Evolution: Digital Assets are getting Physical” – FinTech Worldwide” – https://www.youtube.com/watch?v=1p5PUn4z_Gs

“How the Blockchain revolution will change our lives? | Eddy Travia | TEDxIEMadrid” https://www.youtube.com/watch?v=ErxKm0b0DIU

“How the Blockchain Revolution Will Decentralize Power and End Corruption | Brian Behlendorf” https://www.youtube.com/watch?v=Tv-XR6gXfLI

“Interview for Bitcoin And Blockchain Evolution Podcast – Sarah Herring – “Evolution – There is a Revolution coming!” https://www.youtube.com/watch?v=tIZJsFotDdg

“John McAfee on Infowars: Nothing Can Stop The Blockchain Revolution” – https://www.youtube.com/watch?v=CssU9WBHx6k

“Make the blockchain business case: Evolution, not revolution” (only title, not in video) – PWC – https://www.youtube.com/watch?v=sjr_Wqwk1SI

“The blockchain evolution, from services…to smartphones.” – Mingis on Tech – https://www.youtube.com/watch?v=jvn5zZj5IR8

“The Blockchain Evolution” – Hewlett Packard – https://www.hpe.com/us/en/insights/videos/the-evolution-of-blockchain-1712.html

“The Blockchain Evolution” – https://www.youtube.com/watch?v=TeyeKXmqQn8

“The Blockchain Evolution” – Cambridge House International” – https://www.youtube.com/watch?v=nELBTdqeKuQ

“The Evolution of Bitcoin – Bill Barhydt – Global Summit 2018 | Singularity” Universityhttps://www.youtube.com/watch?v=CZjK1i9CE6U

“The Evolution of Blockchain and Global Vision (Shanghai)” https://www.youtube.com/watch?v=56rOLarCttA

“The Evolution Of Blockchain Over The Decades” – With David Birch” https://www.youtube.com/watch?v=yC8oBJSQ6vc

“The Evolution of Blockchain technology” – Amir Assif. Microsoft Israel” – https://www.youtube.com/watch?v=f_eKp1z5hj0

“The Evolution of Blockchain: How EOS is reinventing blockchain” – https://www.youtube.com/watch?v=R8aDGf8WpKs

“The Evolution of Blockchain” – Nicola Morris – https://www.youtube.com/watch?v=aSy-UJn1G1I

“The Evolution of Blockchain” – The State of Digital Money 18′ conference” – https://www.youtube.com/watch?v=RWfNVTgbqjc

“The Blockchain Revolution – Graham Richter, Accenture” – https://www.youtube.com/watch?v=AYTmjZmsUm4

“The Blockchain Revolution | Rajesh Dhuddu | TEDxHyderabad” – https://www.youtube.com/watch?v=OrnvX92vlu8

“The Blockchain Revolution by Talal Tabaa – ECOH 2018” – https://www.youtube.com/watch?v=AvRJ1kEQ2so

“The Blockchain Revolution Changing the Rules https://www.youtube.com/watch?v=GTgG8XzcVC0

“The Blockchain Revolution in Business and Finance” – https://www.youtube.com/watch?v=3SUfz6p0a7Y

“The blockchain revolution, the ultimate industry disruptor” – https://www.youtube.com/watch?v=7hEiHR-K_KY

“The Blockchain Revolution: From Organisations to Organism | Matan Field | TEDxBreda” – https://www.youtube.com/watch?v=2OSbseTJWfY

[1] https://tim.blog/2017/06/04/nick-szabo/

[2] http://www.businessinsider.com/angellist-ceo-naval-ravikant-shares-his-favorite-books-2015-8

[3] http://www.killingbuddha.co/the-present/2016/10/17/naval-ravikant-on-the-give-and-take-of-the-modern-world

[4] “Being teleological is the second worst thing you can be as a Historian. The worst is being Eurocentric.” – Joel Mokyr

[5] “Biological and Cultural Evolution.” 1984. ICR Monograph Series 20. https://idriesshahfoundation.org/biological-and-cultural-evolution/

[6] Berners-Lee writes of “interconnected groups of people acting as if they shared a larger intuitive brain,” defining social machines on the internet as “processes in which the people do the creative work and the machine does the administration.” (1999) Smart and Shadbolt provide an updated version: “Social Machines are Web-based socio-technical systems in which the human and technological elements play the role of participant machinery with respect to the mechanistic realisation of system level processes.” (2014)

[7] “Extension lectures offered many middle-class women almost their only contact with education beyond the secondary level, and in consequence women came to use the new movement in greater numbers than any other social group, and frequently displayed the greatest personal application.” – Lawrence Goldman (Dons and Workers, 1995: 88)

[8]  A blockchain is “a place [digital ledger] for storing data that is maintained by a network of nodes without anyone in charge.” – Jeremy Clark (2016, https://users.encs.concordia.ca/~clark/talks/2016_edemocracy.pdf)

[9]  See Kevin O’Brien’s (2018) “China, Russia, USA in Race to Use Blockchain for Military Operations.” https://bitcoinist.com/china-russia-usa-blockchain-military/ and Salvador Llopsis Sanchez’ “Blockchain Technology in Defence.” https://www.eda.europa.eu/webzine/issue14/cover-story/blockchain-technology-in-defence

[10] Andrew Braun’s (2018) “Blockchain & Agriculture: A Look at the Issues & Projects Aiming to Solve Them” https://blockonomi.com/blockchain-agriculture/ and “Digging into Blockchain in Agriculture.” https://blockchain.wtf/2018/11/industry-impacts/digging-into-blockchain-in-agriculture/

[11]  Zohar Elhanini’s (2018) “How Blockchain Changed The Art World In 2018.” https://www.forbes.com/sites/zoharelhanani/2018/12/17/how-blockchain-changed-the-art-world-in-2018/#30caa5333074

[12] “Without the need for any central control or mediator blockchains allow for leaderless democracy – a new way of governing human behaviour online through ‘one computer one vote’.” http://kmi.open.ac.uk/projects/name/open-blockchain

[13] “Bitcoin is an immutable evidence system, a ledger that stops fraud.” – Craig Steven Wright https://medium.com/@craig_10243/the-great-mining-swindle-2dec8ffa819d

[14] https://consensys.net/social-impact/

[15] “As a result of the new scientific orthodoxy, the origins of organisms and of artifacts are nowadays seen as radically different: blind natural selection versus the purposive, forward-looking, and intelligent activity of designers.” – Phillip Brey (2008)

[16] However, with the noteworthy possibility that Craig Steve Wright was Satoshi Nakamoto, as he is now claiming, as he did in 2016: “I was Satoshi.” (2019)

[17]  “Evolution and Tinkering.” Science, Vol. 196, No. 4295, June 1977: pp. 1161-1166.

[18] This term was used in 1890 by A.R. Wallace, co-discoverer of ‘natural selection’ with Charles Darwin, to distinguish human-made things from natural organisms, after Darwin’s death.

[19] War and Peace in the Global Village. With Quentin Fiore. New York: Bantam, 1968: p. 19.

[20] “The first Green Revolution enabled developing countries to experience large increases in crop production through the use of fertilisers, pesticides and high-yield crop varieties. Between 1960 and 2000, yields for all developing countries rose 208 per cent for wheat, 109 per cent for rice, 157 per cent for maize, 78 per cent for potatoes and 36 per cent for cassava. This success was most felt with rice growers in Asia and lifted many out of poverty. … Capital investments and agricultural extension services are key for farmers to properly adopt new technologies and raise their farms’ productivity. ” – Liu (2017)

[21] As Joseph Lubin of Ethereum and Consensus says, “She’s big, she can’t go back in.” [21] http://www.theepochtimes.com/n3/668104-the-entrepreneur-joe-lubin-coo-of-ethereum/

Author Information: Jeff Kochan, University of Konstanz, jwkochan@gmail.com.

Kochan, Jeff. “Decolonising Science in Canada: A Work in Progress.” Social Epistemology Review and Reply Collective 7, no. 11 (2018): 42-47.

The pdf of the article gives specific page numbers. Shortlink: https://wp.me/p1Bfg0-43i

A Mi’kmaw man and woman in ceremonial clothing.
Image by Shawn Harquail via Flickr / Creative Commons

 

This essay is in reply to:

Wills, Bernard (2018). ‘Weak Scientism: The Prosecution Rests.’ Social Epistemology Review & Reply Collective 7(10): 31-36.

In a recent debate about scientism in the SERRC pages, Bernard Wills challenges the alleged ‘ideological innocence’ of scientism by introducing a poignant example from his own teaching experience on the Grenfell Campus of Memorial University, in Corner Brook, Newfoundland (Wills 2018: 33).

Note that Newfoundland, among its many attractions, claims a UNESCO World Heritage site called L’Anse aux Meadows. Dating back about 1000 years, L’Anse aux Meadows is widely agreed to hold archaeological evidence for the earliest encounters between Europeans and North American Indigenous peoples.

Southwest Newfoundland is a part of Mi’kma’ki, the traditional territory of the Mi’kmaq. This territory also includes Nova Scotia, Prince Edward Island, and parts of New Brunswick, Québec, and Maine. Among North America’s Indigenous peoples, the Mi’kmaq can readily claim to have experienced some of the earliest contact with European culture.

Creeping Colonialism in Science

Let us now turn to Wills’s example. A significant number of students on the Grenfell Campus are Mi’kmaq. These students have sensitised Wills to the fact that science has been used by the Canadian state as an instrument for colonial oppression. By cloaking colonialism in the claim that science is a neutral, universal standard by which to judge the validity of all knowledge claims, state scientism systematically undermines the epistemic authority of ancient Mi’kmaq rights and practices.

Wills argues, ‘[t]he fact that Indigenous knowledge traditions are grounded in local knowledge, in traditional lore and in story means that on questions of importance to them Indigenous peoples cannot speak. It means they have to listen to others who “know better” because the propositions they utter have the form of science.’ Hence, Wills concludes that, in the Canadian context, the privileging of science over Indigenous knowledge ‘is viciously exploitative and intended to keep indigenous peoples in a place of dependency and inferiority’ (Wills 2018: 33-4).

There is ample historical and ethnographic evidence available to support Wills’s claims. John Sandlos, for example, has shown how the Canadian state, from the late 19th century to around 1970, used wildlife science as a ‘coercive’ and ‘totalizing influence’ in order to assert administrative control over Indigenous lives and lands in Northern Canada (Sandlos 2007: 241, 242).

Paul Nadasdy, in turn, has argued that more recent attempts by the Canadian state to establish wildlife co-management relationships with Indigenous groups are but ‘subtle extensions of empire, replacing local Aboriginal ways of talking, thinking and acting with those specifically sanctioned by the state’ (Nadasdy 2005: 228). The suspicions of Wills’s Mi’kmaw students are thus well justified by decades of Canadian state colonial practice.

Yet Indigenous peoples in Canada have also pointed out that, while this may be most of the story, it is not the whole story. For example, Wills cites Deborah Simmons in support of his argument that the Canadian state uses science to silence Indigenous voices (Wills 2018: 33n4). Simmons certainly does condemn the colonial use of science in the article Wills cites, but she also writes: ‘I’ve seen moments when there is truly a hunger for new knowledge shared by indigenous people and scientists, and cross-cultural barriers are overcome to discuss research questions and interpret results from the two distinct processes of knowledge production’ (Simmons 2010).

Precious Signs of Hope Amid Conflict

In the haystack of Canada’s ongoing colonial legacy, it can often be very difficult to detect such slivers of co-operation between scientists and Indigenous peoples. For example, after three decades of periodic field work among the James Bay Cree, Harvey Feit still found it difficult to accept Cree claims that they had once enjoyed a long-term, mutually beneficial relationship with the Canadian state in respect of wildlife management in their traditional hunting territories. But when Feit finally went into the archives, he discovered that it was true (Feit 2005: 269; see also the discussion in Kochan 2015: 9-10).

In a workshop titled Research the Indigenous Way, part of the 2009 Northern Governance and Policy Research Conference, held in Yellowknife, Northwest Territories, participants affirmed that ‘Indigenous people have always been engaged in research processes as part of their ethical “responsibility to keep the land alive”’ (McGregor et al. 2010: 102). At the same time, participants also recognised Indigenous peoples’ ‘deep suspicion’ of research as a vehicle for colonial exploitation (McGregor et al. 2010: 118).

Yet, within this conflicted existential space, workshop participants still insisted that there had been, in the last 40 years, many instances of successful collaborative research between Indigenous and non-Indigenous practitioners in the Canadian North. According to one participant, Alestine Andre, these collaborations, although now often overlooked, ‘empowered and instilled a sense of well-being, mental, physical, emotional, spiritual good health in their Elders, youth and community people’ (McGregor et al. 2010: 108).

At the close of the workshop, participants recommended that research not be rejected, but instead indigenised, that is, put into the hands of Indigenous practitioners ‘who bear unique skills for working in the negotiated space that bridges into and from scientific and bureaucratic ways of knowing’ (McGregor et al. 2010: 119). Indigenised research should both assert and strengthen Indigenous rights and self-government.

Furthermore, within this indigenised research context, ‘there is a role for supportive and knowledgeable non-Indigenous researchers, but […] these would be considered “resource people” whose imported research interests and methods are supplementary to the core questions and approach’ (McGregor et al. 2010: 119).

Becoming a non-Indigenous ‘resource person’ in the context of decolonising science can be challenging work, and may offer little professional reward. As American archaeologist, George Nicholas, observes, it ‘requires more stamina and thicker skin than most of us, including myself, are generally comfortable with – and it can even be harmful, whether one is applying for permission to work on tribal lands or seeking academic tenure’ (Nicholas 2004: 32).

Indigenous scholar Michael Marker, at the University of British Columbia, has likewise suggested that such research collaborations require patience: in short, ‘don’t rush!’ (cited by Wylie 2018). Carly Dokis and Benjamin Kelly, both of whom study Indigenous water-management practices in Northern Ontario, also emphasise the importance of listening, of ‘letting go of your own timetable and relinquishing control of your project’ (Dokis & Kelly 2014: 2). Together with community-based researchers, Dokis and Kelly are exploring new research methodologies, above all the use of ‘storycircles’ (https://faculty.nipissingu.ca/carlyd/research/).

Such research methods are also being developed elsewhere in Canada. The 2009 Research the Indigenous Way workshop, mentioned above, was structured as a ‘sharing circle,’ a format that, according to the workshop facilitators, ‘reflect[ed] the research paradigm being talked about’ (McGregor et al. 2010: 101). Similarly, the 13th North American Caribou Workshop a year later, in Winnipeg, Manitoba, included an ‘Aboriginal talking circle,’ in which experiences and ideas about caribou research were shared over the course of one and a half days. The ‘relaxed pace’ of the talking circle ‘allowed for a gradual process of relationship-building among the broad spectrum of Aboriginal nations, while providing a scoping of key issues in caribou research and stewardship’ (Simmons et al. 2012: 18).

Overcoming a Rational Suspicion

One observation shared by many participants in the caribou talking circle was the absence of Indigenous youth in scientific discussions. According to the facilitators, an important lesson learned from the workshop was that youth need to be part of present and future caribou research in order for Indigenous knowledge to survive (Simmons et al. 2012: 19).

This problem spans the country and all scientific fields. As Indigenous science specialist Leroy Little Bear notes, the Canadian Royal Commission on Aboriginal Peoples (1991-1996) ‘found consistent criticism among Aboriginal people in the lack of curricula in schools that were complimentary to Aboriginal peoples’ (Little Bear 2009: 17).

This returns us to Wills’s Mi’kmaw students at the Grenfell Campus in Corner Brook. A crucial element in decolonising scientific research in Canada is the encouragement of Indigenous youth interest in scientific ways of knowing nature. Wills’s observation that Mi’kmaw students harbour a keen suspicion of science as an instrument of colonial oppression points up a major obstacle to this community process. Under present circumstances, Indigenous students are more likely to drop out of, rather than to tune into, the science curricula being taught at their schools and universities.

Mi’kmaw educators and scholars are acutely aware of this problem, and they have worked assiduously to overcome it. In the 1990s, a grass-roots initiative between members of the Mi’kmaw Eskasoni First Nation and a handful of scientists at nearby Cape Breton University (CBU), in Nova Scotia, began to develop and promote a new ‘Integrative Science’ programme for CBU’s syllabus. Their goal was to reverse the almost complete absence of Indigenous students in CBU’s science-based courses by including Mi’kmaw and other Indigenous knowledges alongside mainstream science within the CBU curriculum (Bartlett et al. 2012: 333; see also Hatcher et al. 2009).

In Fall Term 2001, Integrative Science (in Mi’kmaw, Toqwa’tu’kl Kjijitaqnn, or ‘bringing our knowledges together’) became an accredited university degree programme within CBU’s already established 4-year Bachelor of Science Community Studies (BScCS) degree (see: http://www.integrativescience.ca). In 2008, however, the suite of courses around which the programme had been built was disarticulated from both the BScSC and the Integrative Science concentration, and was instead offered within ‘access programming’ for Indigenous students expressing interest in a Bachelor of Arts degree. The content of the courses was also shifted to mainstream science (Bartlett et al. 2012: 333).

Throughout its 7-year existence, the Integrative Science academic programme faced controversy within CBU; it was never assigned a formal home department or budget (Bartlett et al. 2012: 333). Nevertheless, the programme succeeded in meeting its original goal. Over those 7 years, 27 Mi’kmaw students with some programme affiliation graduated with a science or science-related degree, 13 of them with a BScSC concentration in Integrative Science.

In 2012, most of these 13 graduates held key service positions within their home communities (e.g., school principal, research scientist or assistant, job coach, natural resource manager, nurse, teacher). These numbers compare favourably with the fewer than 5 Indigenous students who graduated with a science or science-related degree, unaffiliated with Integrative Science, both before and during the life of the programme (Bartlett et al. 2012: 334). All told, up to 2007, about 100 Mi’kmaw students had participated in first-year Integrative Science courses at CBU (Bartlett et al. 2012: 334).

From its inception, Integrative Science operated under an axe, facing, among other things, chronic ‘inconsistencies and insufficiencies at the administrative, faculty, budgetary and recruitment levels’ (Bartlett 2012: 38). One could lament its demise as yet one more example of the colonialism that Wills has brought to our attention in respect of the Grenfell Campus in Corner Brook. Yet it is important to note that the culprit here was not science, as such, but a technocratic – perhaps scientistic – university bureaucracy. In any case, it seems inadequate to chalk up the travails of Integrative Science to an indiscriminate search for administrative ‘efficiencies’ when the overall nation-state context was and is, in my opinion, a discriminatory one.

When Seeds Are Planted, Change Can Come

But this is not the note on which I would like to conclude. To repeat, up to 2007, about 100 Mi’kmaw students had participated in first-year Integrative Science courses. That is about 100 Mi’kmaw students who are, presumably, less likely to hold the firmly negative attitude towards science that Wills has witnessed among his own Mi’kmaw students in Newfoundland.

As I wrote above, in the haystack of Canada’s ongoing colonial legacy, it can be very difficult to detect those rare slivers of co-operation between scientists and Indigenous peoples on which I have here tried to shine a light. If this light were allowed to go out, a sense of hopelessness could follow, and then an allegedly hard border between scientific and Indigenous knowledges may suddenly spring up and appear inevitable, if also, for some, lamentable.

Let me end with the words of Albert Marshall, who, at least up to 2012, was the designated voice on environmental matters for Mi’kmaw Elders in Unama’ki (Cape Breton), as well as a member of the Moose Clan. Marshall was a key founder and constant shepherd of CBU’s Integrative Science degree programme. One last time: some 100 Mi’kmaw students participated in that programme during its brief life. Paraphrased by his CBU collaborator, Marilyn Iwama, Elder Marshall had this to say:

Every year, the ash tree drops its seeds on the ground. Sometimes those seeds do not germinate for two, three or even four cycles of seasons. If the conditions are not right, the seeds will not germinate. […] [Y]ou have to be content to plant seeds and wait for them to germinate. You have to wait out the period of dormancy. Which we shouldn’t confuse with death. We should trust this process. (Bartlett et al. 2015: 289)

Contact details: jwkochan@gmail.com

References

Bartlett, Cheryl (2012). ‘The Gift of Multiple Perspectives in Scholarship.’ University Affairs / Affaires universitaires 53(2): 38.

Bartlett, Cheryl, Murdena Marshall, Albert Marshall and Marilyn Iwama (2015). ‘Integrative Science and Two-Eyed Seeing: Enriching the Discussion Framework for Healthy Communities.’ In Lars K. Hallstrom, Nicholas Guehlstorf and Margot Parkes (eds), Ecosystems, Society and Health: Pathways through Diversity, Convergence and Integration (Montréal: McGill-Queens University Press), pp. 280-326.

Bartlett, Cheryl, Murdena Marshall and Albert Marshall (2012). ‘Two-Eyed Seeing and Other Lessons Learned within a Co-Learning Journey of Bringing Together Indigenous and Mainstream Knowledges and Ways of Knowing.’ Journal of Environmental Studies and Sciences 2: 331-340.

Dokis, Carly and Benjamin Kelly (2014). ‘Learning to Listen: Reflections on Fieldwork in First Nation Communities in Canada.’ Canadian Association of Research Ethics Boards Pre and Post (Sept): 2-3.

Feit, Harvey A. (2005). ‘Re-Cognizing Co-Management as Co-Governance: Visions and Histories of Conservation at James Bay.’ Anthropologica 47: 267-288.

Hatcher, Annamarie, Cheryl Bartlett, Albert Marshall and Murdena Marshall (2009). ‘Two-Eyed Seeing in the Classroom Environment: Concepts, Approaches, and Challenges.’ Canadian Journal of Science, Mathematics and Technology Education 9(3): 141-153.

Kochan, Jeff (2015). ‘Objective Styles in Northern Field Science.’ Studies in the History and Philosophy of Science 52: 1-12. https://doi.org/10.1016/j.shpsa.2015.04.001

Little Bear, Leroy (2009). Naturalizing Indigenous Knowledge, Synthesis Paper. University of Saskatchewan, Aboriginal Education Research Centre, Saskatoon, Sask. and First Nations and Adult Higher Education Consortium, Calgary, Alta. https://www.afn.ca/uploads/files/education/21._2009_july_ccl-alkc_leroy_littlebear_naturalizing_indigenous_knowledge-report.pdf  [Accessed 05 November 2018]

McGregor, Deborah, Walter Bayha & Deborah Simmons (2010). ‘“Our Responsibility to Keep the Land Alive”: Voices of Northern Indigenous Researchers.’ Pimatisiwin: A Journal of Aboriginal and Indigenous Community Health 8(1): 101-123.

Nadasdy, Paul (2005). ‘The Anti-Politics of TEK: The Institutionalization of Co-Management Discourse and Practice.’ Anthropologica 47: 215-232.

Nicholas, George (2004). ‘What Do I Really Want from a Relationship with Native Americans?’ The SAA Archaeological Record (May): 29-33.

Sandlos, John (2007). Hunters at the Margin: Native People and Wildlife Conservation in the Northwest Territories (Vancouver: UBC Press).

Simmons, Deborah (2010). ‘Residual Stalinism.’ Upping the Anti #11. http://uppingtheanti.org/journal/article/11-residual-stalinism [Accessed 01 November 2018]

Simmons, Deborah, Walter Bayha, Danny Beaulieu, Daniel Gladu & Micheline Manseau (2012). ‘Aboriginal Talking Circle: Aboriginal Perspectives on Caribou Conservation (13th North American Caribou Workshop).’ Rangifer, Special Issue #20: 17-19.

Wills, Bernard (2018). ‘Weak Scientism: The Prosecution Rests.’ Social Epistemology Review & Reply Collective 7(10): 31-36.

Wylie, Alison (2018). ‘Witnessing and Translating: The Indigenous/Science Project.’ Keynote address at the workshop Philosophy, Archaeology and Community Perspectives: Finding New Ground, University of Konstanz, 22 October 2018.

 

Author Information: Raphael Sassower, University of Colorado, Colorado Springs, rsasswe@uccs.edu.

Sassower, Raphael. “Post-Truths and Inconvenient Facts.” Social Epistemology Review and Reply Collective 7, no. 8 (2018): 47-60.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-40g

Can one truly refuse to believe facts?
Image by Oxfam International via Flickr / Creative Commons

 

If nothing else, Steve Fuller has his ear to the pulse of popular culture and the academics who engage in its twists and turns. Starting with Brexit and continuing into the Trump-era abyss, “post-truth” was dubbed by the OED as its word of the year in 2016. Fuller has mustered his collected publications to recast the debate over post-truth and frame it within STS in general and his own contributions to social epistemology in particular.

This could have been a public mea culpa of sorts: we, the community of sociologists (and some straggling philosophers and anthropologists and perhaps some poststructuralists) may seem to someone who isn’t reading our critiques carefully to be partially responsible for legitimating the dismissal of empirical data, evidence-based statements, and the means by which scientific claims can be deemed not only credible but true. Instead, we are dazzled by a range of topics (historically anchored) that explain how we got to Brexit and Trump—yet Fuller’s analyses of them don’t ring alarm bells. There is almost a hidden glee that indeed the privileged scientific establishment, insular scientific discourse, and some of its experts who pontificate authoritative consensus claims are all bound to be undone by the rebellion of mavericks and iconoclasts that include intelligent design promoters and neoliberal freedom fighters.

In what follows, I do not intend to summarize the book, as it is short and entertaining enough for anyone to read on their own. Instead, I wish to outline three interrelated points that one might argue need not be argued but, apparently, do: 1) certain critiques of science have contributed to the Trumpist mindset; 2) the politics of Trumpism is too dangerous to be sanguine about; 3) the post-truth condition is troublesome and insidious. Though Fuller deals with some of these issues, I hope to add some constructive clarification to them.

Part One: Critiques of Science

As Theodor Adorno reminds us, critique is essential not only for philosophy, but also for democracy. He is aware that the “critic becomes a divisive influence, with a totalitarian phrase, a subversive” (1998/1963, 283) insofar as the status quo is being challenged and sacred political institutions might have to change. The price of critique, then, can be high, and therefore critique should be managed carefully and only cautiously deployed. Should we refrain from critique, then? Not at all, continues Adorno.

But if you think that a broad, useful distinction can be offered among different critiques, think again: “[In] the division between responsible critique, namely, that practiced by those who bear public responsibility, and irresponsible critique, namely, that practiced by those who cannot be held accountable for the consequences, critique is already neutralized.” (Ibid. 285) Adorno’s worry is not only that one forgets that “the truth content of critique alone should be that authority [that decides if it’s responsible],” but that when such a criterion is “unilaterally invoked,” critique itself can lose its power and be at the service “of those who oppose the critical spirit of a democratic society.” (Ibid)

In a political setting, the charge of irresponsible critique shuts the conversation down and ensures political hegemony without disruptions. Modifying Adorno’s distinction between (politically) responsible and irresponsible critiques, responsible scientific critiques are constructive insofar as they attempt to improve methods of inquiry, data collection and analysis, and contribute to the accumulated knowledge of a community; irresponsible scientific critiques are those whose goal is to undermine the very quest for objective knowledge and the means by which such knowledge can be ascertained. Questions about the legitimacy of scientific authority are related to but not of exclusive importance for these critiques.

Have those of us committed to the critique of science missed the mark of the distinction between responsible and irresponsible critiques? Have we become so subversive and perhaps self-righteous that science itself has been threatened? Though Fuller is primarily concerned with the hegemony of the sociology of science studies and the movement he has championed under the banner of “social epistemology” since the 1980s, he does acknowledge the Popperians and their critique of scientific progress and even admires the Popperian contribution to the scientific enterprise.

But he is reluctant to recognize the contributions of Marxists, poststructuralists, and postmodernists who have been critically engaging the power of science since the 19th century. Among them, we find Jean-François Lyotard who, in The Postmodern Condition (1984/1979), follows Marxists and neo-Marxists who have regularly lumped science and scientific discourse with capitalism and power. This critical trajectory has been well rehearsed, so suffice it here to say, SSK, SE, and the Edinburgh “Strong Programme” are part of a long and rich critical tradition (whose origins are Marxist). Adorno’s Frankfurt School is part of this tradition, and as we think about science, which had come to dominate Western culture by the 20th century (in the place of religion, whose power had by then waned as the arbiter of truth), it was its privileged power and interlocking financial benefits that drew the ire of critics.

Were these critics “responsible” in Adorno’s political sense? Can they be held accountable for offering (scientific and not political) critiques that improve the scientific process of adjudication between criteria of empirical validity and logical consistency? Not always. Did they realize that their success could throw the baby out with the bathwater? Not always. While Fuller grants Karl Popper the upper hand (as compared to Thomas Kuhn) when indirectly addressing such questions, we must keep an eye on Fuller’s “baby.” It’s easy to overlook the slippage from the political to the scientific and vice versa: Popper’s claim that we never know the Truth doesn’t mean that his (and our) quest for discovering the Truth as such is given up, it’s only made more difficult as whatever is scientifically apprehended as truth remains putative.

Limits to Skepticism

What is precious about the baby—science in general, and scientific discourse and its community in more particular ways—is that it offered safeguards against frivolous skepticism. Robert Merton (1973/1942) famously outlined the four features of the scientific ethos, principles that characterized the ideal workings of the scientific community: universalism, communism (communalism, as per the Cold War terror), disinterestedness, and organized skepticism. It is the last principle that is relevant here, since it unequivocally demands an institutionalized mindset of putative acceptance of any hypothesis or theory that is articulated by any community member.

One detects the slippery slope that would move one from being on guard when engaged with any proposal to being so skeptical as to never accept any proposal no matter how well documented or empirically supported. Al Gore, in his An Inconvenient Truth (2006), sounded the alarm about climate change. A dozen years later we are still plagued by climate-change deniers who refuse to look at the evidence, suggesting instead that the standards of science themselves—from the collection of data in the North Pole to computer simulations—have not been sufficiently fulfilled (“questions remain”) to accept human responsibility for the increase of the earth’s temperature. Incidentally, here is Fuller’s explanation of his own apparent doubt about climate change:

Consider someone like myself who was born in the midst of the Cold War. In my lifetime, scientific predictions surrounding global climate change has [sic.] veered from a deep frozen to an overheated version of the apocalypse, based on a combination of improved data, models and, not least, a geopolitical paradigm shift that has come to downplay the likelihood of a total nuclear war. Why, then, should I not expect a significant, if not comparable, alteration of collective scientific judgement in the rest of my lifetime? (86)

Expecting changes in the model does not entail a) that no improved model can be offered; b) that methodological changes in themselves are a bad thing (they might be, rather, improvements); or c) that one should not take action at all based on the current model because in the future the model might change.

The Royal Society of London (1660) set the benchmark of scientific credibility low when it accepted as scientific evidence any report by two independent witnesses. As the years went by, testability (“confirmation,” for the Vienna Circle, “falsification,” for Popper) and repeatability were added as requirements for a report to be considered scientific, and by now, various other conditions have been proposed. Skepticism, organized or personal, remains at the very heart of the scientific march towards certainty (or at least high probability), but when used perniciously, it has derailed reasonable attempts to use science as a means by which to protect, for example, public health.

Both Michael Bowker (2003) and Robert Proctor (1995) chronicle cases where asbestos and cigarette lobbyists and lawyers alike were able to sow enough doubt in the name of attenuated scientific data collection to ward off regulators, legislators, and the courts for decades. Instead of finding sufficient empirical evidence to attribute asbestos and nicotine to the failing health condition (and death) of workers and consumers, “organized skepticism” was weaponized to fight the sick and protect the interests of large corporations and their insurers.

Instead of buttressing scientific claims (that have passed the tests—in refereed professional conferences and publications, for example—of most institutional scientific skeptics), organized skepticism has been manipulated to ensure that no claim is ever scientific enough or has the legitimacy of the scientific community. In other words, what should have remained the reasonable cautionary tale of a disinterested and communal activity (that could then be deemed universally credible) has turned into a circus of fire-blowing clowns ready to burn down the tent. The public remains confused, not realizing that just because the stakes have risen over the decades does not mean there are no standards that ever can be met. Despite lobbyists’ and lawyers’ best efforts of derailment, courts have eventually found cigarette companies and asbestos manufacturers guilty of exposing workers and consumers to deathly hazards.

Limits to Belief

If we add to this logic of doubt, which has been responsible for discrediting science and the conditions for proposing credible claims, a bit of U.S. cultural history, we may enjoy a more comprehensive picture of the unintended consequences of certain critiques of science. Citing Kurt Andersen (2017), Robert Darnton suggests that the Enlightenment’s “rational individualism interacted with the older Puritan faith in the individual’s inner knowledge of the ways of Providence, and the result was a peculiarly American conviction about everyone’s unmediated access to reality, whether in the natural world or the spiritual world. If we believe it, it must be true.” (2018, 68)

This way of thinking—unmediated experiences and beliefs, unconfirmed observations, and disregard of others’ experiences and beliefs—continues what Richard Hofstadter (1962) dubbed “anti-intellectualism.” For Americans, this predates the republic and is characterized by a hostility towards the life of the mind (admittedly, at the time, religious texts), critical thinking (self-reflection and the rules of logic), and even literacy. The heart (our emotions) can more honestly lead us to the Promised Land, whether it is heaven on earth in the Americas or the Christian afterlife; any textual interference or reflective pondering is necessarily an impediment, one to be suspicious of and avoided.

This lethal combination of the life of the heart and righteous individualism brings about general ignorance and what psychologists call “confirmation bias” (the view that we endorse what we already believe to be true regardless of countervailing evidence). The critique of science, along this trajectory, can be but one of many so-called critiques of anything said or proven by anyone whose ideology we do not endorse. But is this even critique?

Adorno would find this a charade, a pretense that poses as a critique but in reality is a simple dismissal without intellectual engagement, a dogmatic refusal to listen and observe. He definitely would be horrified by Stephen Colbert’s oft-quoted quip on “truthiness” as “the conviction that what you feel to be true must be true.” Even those who resurrect Daniel Patrick Moynihan’s phrase, “You are entitled to your own opinion, but not to your own facts,” quietly admit that his admonishment is ignored by media more popular than informed.

On Responsible Critique

But surely there is merit to responsible critiques of science. Weren’t many of these critiques meant to dethrone the unparalleled authority claimed in the name of science, as Fuller admits all along? Wasn’t Lyotard (and Marx before him), for example, correct in pointing out the conflation of power and money in the scientific vortex that could legitimate whatever profit-maximizers desire? In other words, should scientific discourse be put on par with other discourses?  Whose credibility ought to be challenged, and whose truth claims deserve scrutiny? Can we privilege or distinguish science if it is true, as Monya Baker has reported, that “[m]ore than 70% of researchers have tried and failed to reproduce another scientist’s experiments, and more than half have failed to reproduce their own experiments” (2016, 1)?

Fuller remains silent about these important and responsible questions about the problematics (methodologically and financially) of reproducing scientific experiments. Baker’s report cites Nature‘s survey of 1,576 researchers and reveals “sometimes-contradictory attitudes towards reproducibility. Although 52% of those surveyed agree that there is a significant ‘crisis’ of reproducibility, less than 31% think that failure to reproduce published results means that the result is probably wrong, and most say that they still trust the published literature.” (Ibid.) So, if science relies on reproducibility as a cornerstone of its legitimacy (and superiority over other discourses), and if the results are so dismal, should it not be discredited?

One answer, given by Hans E. Plesser, suggests that there is a confusion between the notions of repeatability (“same team, same experimental setup”), replicability (“different team, same experimental setup”), and reproducibility (“different team, different experimental setup”). If understood in these terms, it stands to reason that one may not get the same results all the time and that this fact alone does not discredit the scientific enterprise as a whole. Nuanced distinctions take us down a scientific rabbit-hole most post-truth advocates refuse to follow. These nuances are lost on a public that demands to know the “bottom line” in brief sound bites: Is science scientific enough, or is it bunk? When can we trust it?

Trump excels at this kind of rhetorical device: repeat a falsehood often enough and people will believe it; and because individual critical faculties are not a prerequisite for citizenship, post-truth means no truth, or whatever the president says is true. Adorno’s distinction of the responsible from the irresponsible political critics comes into play here; but he innocently failed to anticipate the Trumpian move to conflate the political and scientific and pretend as if there is no distinction—methodologically and institutionally—between political and scientific discourses.

With this cultural backdrop, many critiques of science have undermined its authority and thereby lent credence to any dismissal of science (legitimately by insiders and perhaps illegitimately at times by outsiders). Sociologists and postmodernists alike forgot to put warning signs on their academic and intellectual texts: Beware of hasty generalizations! Watch out for wolves in sheep clothes! Don’t throw the baby out with the bathwater!

One would think such advisories unnecessary. Yet without such safeguards, internal disputes and critical investigations appear to have unintentionally discredited the entire scientific enterprise in the eyes of post-truth promoters, the Trumpists whose neoliberal spectacles filter in dollar signs and filter out pollution on the horizon. The discrediting of science has become a welcome distraction that opens the way to radical free-market mentality, spanning from the exploitation of free speech to resource extraction to the debasement of political institutions, from courts of law to unfettered globalization. In this sense, internal (responsible) critiques of the scientific community and its internal politics, for example, unfortunately license external (irresponsible) critiques of science, the kind that obscure the original intent of responsible critiques. Post-truth claims at the behest of corporate interests sanction a free for all where the concentrated power of the few silences the concerns of the many.

Indigenous-allied protestors block the entrance to an oil facility related to the Kinder-Morgan oil pipeline in Alberta.
Image by Peg Hunter via Flickr / Creative Commons

 

Part Two: The Politics of Post-Truth

Fuller begins his book about the post-truth condition that permeates the British and American landscapes with a look at our ancient Greek predecessors. According to him, “Philosophers claim to be seekers of the truth but the matter is not quite so straightforward. Another way to see philosophers is as the ultimate experts in a post-truth world” (19). This means that those historically entrusted to be the guardians of truth in fact “see ‘truth’ for what it is: the name of a brand ever in need of a product which everyone is compelled to buy. This helps to explain why philosophers are most confident appealing to ‘The Truth’ when they are trying to persuade non-philosophers, be they in courtrooms or classrooms.” (Ibid.)

Instead of being the seekers of the truth, thinkers who care not about what but how we think, philosophers are ridiculed by Fuller (himself a philosopher turned sociologist turned popularizer and public relations expert) as marketing hacks in a public relations company that promotes brands. Their serious dedication to finding the criteria by which truth is ascertained is used against them: “[I]t is not simply that philosophers disagree on which propositions are ‘true’ or ‘false’ but more importantly they disagree on what it means to say that something is ‘true’ or ‘false’.” (Ibid.)

Some would argue that the criteria by which propositions are judged to be true or false are worthy of debate, rather than the cavalier dismissal of Trumpists. With criteria in place (even if only by convention), at least we know what we are arguing about, as these criteria (even if contested) offer a starting point for critical scrutiny. And this, I maintain, is a task worth performing, especially in the age of pluralism when multiple perspectives constitute our public stage.

In addition to debasing philosophers, it seems that Fuller reserves a special place in purgatory for Socrates (and Plato) for labeling the rhetorical expertise of the sophists—“the local post-truth merchants in fourth century BC Athens”—negatively. (21) It becomes obvious that Fuller is “on their side” and that the presumed debate over truth and its practices is in fact nothing but “whether its access should be free or restricted.” (Ibid.) In this neoliberal reading, it is all about money: are sophists evil because they charge for their expertise? Is Socrates a martyr and saint because he refused payment for his teaching?

Fuller admits, “Indeed, I would have us see both Plato and the Sophists as post-truth merchants, concerned more with the mix of chance and skill in the construction of truth than with the truth as such.” (Ibid.) One wonders not only if Plato receives fair treatment (reminiscent of Popper’s denigration of Plato as supporting totalitarian regimes, while sparing Socrates as a promoter of democracy), but whether calling all parties to a dispute “post-truth merchants” obliterates relevant differences. In other words, have we indeed lost the desire to find the truth, even if it can never be the whole truth and nothing but the truth?

Political Indifference to Truth

One wonders how far this goes: political discourse without any claim to truth conditions would become nothing but a marketing campaign where money and power dictate the acceptance of the message. Perhaps the intended message here is that contemporary cynicism towards political discourse has its roots in ancient Greece. Regardless, one should worry that such cynicism indirectly sanctions fascism.

Can the poor and marginalized in our society afford this kind of cynicism? For them, unlike their privileged counterparts in the political arena, claims about discrimination and exploitation, about unfair treatment and barriers to voting are true and evidence based; they are not rhetorical flourishes by clever interlocutors.

Yet Fuller would have none of this. For him, political disputes are games:

[B]oth the Sophists and Plato saw politics as a game, which is to say, a field of play involving some measure of both chance and skill. However, the Sophists saw politics primarily as a game of chance whereas Plato saw it as a game of skill. Thus, the sophistically trained client deploys skill in [the] aid of maximizing chance occurrences, which may then be converted into opportunities, while the philosopher-king uses much the same skills to minimize or counteract the workings of chance. (23)

Fuller could be channeling here twentieth-century game theory and its application in the political arena, or the notion offered by Lyotard when describing the minimal contribution we can make to scientific knowledge (where we cannot change the rules of the game but perhaps find a novel “move” to make). Indeed, if politics is deemed a game of chance, then anything goes, and it really should not matter if an incompetent candidate like Trump ends up winning the American presidency.

But is it really a question of skill and chance? Or, as some political philosophers would argue, is it not a question of the best means by which to bring to fruition the best results for the general wellbeing of a community? The point of suggesting the figure of a philosopher-king, to be sure, was not his rhetorical skills in this conjunction, but instead the deep commitment to rule justly, to think critically about policies, and to treat constituents with respect and fairness. Plato’s Republic, however criticized, was supposed to be about justice, not about expediency; it is an exploration of the rule of law and wisdom, not a manual about manipulation. If the recent presidential election in the US taught us anything, it’s that we should be wary of political gamesmanship and focus on experience and knowledge, vision and wisdom.

Out-Gaming Expertise Itself

Fuller would have none of this, either. It seems that there is virtue in being a “post-truther,” someone who can easily switch between knowledge games, unlike the “truther” whose aim is to “strengthen the distinction by making it harder to switch between knowledge games.” (34) In the post-truth realm, then, knowledge claims are lumped into games that can be played at will, that can be substituted when convenient, without a hint of the danger such capricious game-switching might engender.

It’s one thing to challenge a scientific hypothesis about astronomy because the evidence is still unclear (as Stephen Hawking has done in regard to Black Holes) and quite another to compare it to astrology (and give equal hearings to horoscope and Tarot card readers as to physicists). Though we are far from the Demarcation Problem (between science and pseudo-science) of the last century, this does not mean that there is no difference at all between different discourses and their empirical bases (or that the problem itself isn’t worthy of reconsideration in the age of Fuller and Trump).

On the contrary, it’s because we assume difference between discourses (gray as they may be) that we can move on to figure out on what basis our claims can and should rest. The danger, as we see in the political logic of the Trump administration, is that friends become foes (European Union) and foes are admired (North Korea and Russia). Game-switching in this context can lead to a nuclear war.

In Fuller’s hands, though, something else is at work. Speaking of contemporary political circumstances in the UK and the US, he says: “After all, the people who tend to be demonized as ‘post-truth’ – from Brexiteers to Trumpists – have largely managed to outflank the experts at their own game, even if they have yet to succeed in dominating the entire field of play.” (39) Fuller’s celebratory tone here may either bring a slight warning in the use of “yet” before the success “in dominating the entire field of play” or a prediction that indeed this is what is about to happen soon enough.

The neoliberal bottom-line surfaces in this assessment: he who wins must be right, the rich must be smart, and more perniciously, the appeal to truth is beside the point. More specifically, Fuller continues:

My own way of dividing the ‘truthers’ and the ‘post-truthers’ is in terms of whether one plays by the rules of the current knowledge game or one tries to change the rules of the game to one’s advantage. Unlike the truthers, who play by the current rules, the post-truthers want to change the rules. They believe that what passes for truth is relative to the knowledge game one is playing, which means that depending on the game being played, certain parties are advantaged over others. Post-truth in this sense is a recognisably social constructivist position, and many of the arguments deployed to advance ‘alternative facts’ and ‘alternative science’ nowadays betray those origins. They are talking about worlds that could have been and still could be—the stuff of modal power. (Ibid.)

By now one should be terrified. This is a strong endorsement of lying as a matter of course, as a way to distract from the details (and empirical bases) of one “knowledge game”—because it may not be to one’s ideological liking–in favor of another that might be deemed more suitable (for financial or other purposes).

The political stakes here are too high to ignore, especially because there are good reasons why “certain parties are advantaged over others” (say, climate scientists “relative to” climate deniers who have no scientific background or expertise). One wonders what it means to talk about “alternative facts” and “alternative science” in this context: is it a means of obfuscation? Is it yet another license granted by the “social constructivist position” not to acknowledge the legal liability of cigarette companies for the addictive power of nicotine? Or the pollution of water sources in Flint, Michigan?

What Is the Mark of an Open Society?

If we corral the broader political logic at hand to the governance of the scientific community, as Fuller wishes us to do, then we hear the following:

In the past, under the inspiration of Karl Popper, I have argued that fundamental to the governance of science as an ‘open society’ is the right to be wrong (Fuller 2000a: chap. 1). This is an extension of the classical republican ideal that one is truly free to speak their mind only if they can speak with impunity. In the Athenian and the Roman republics, this was made possible by the speakers–that is, the citizens–possessing independent means which allowed them to continue with their private lives even if they are voted down in a public meeting. The underlying intuition of this social arrangement, which is the epistemological basis of Mill’s On Liberty, is that people who are free to speak their minds as individuals are most likely to reach the truth collectively. The entangled histories of politics, economics and knowledge reveal the difficulties in trying to implement this ideal. Nevertheless, in a post-truth world, this general line of thought is not merely endorsed but intensified. (109)

To be clear, Fuller not only asks for the “right to be wrong,” but also for the legitimacy of the claim that “people who are free to speak their minds as individuals are most likely to reach the truth collectively.” The first plea is reasonable enough, as humans are fallible (yes, Popper here), and the history of ideas has proven that killing heretics is counterproductive (and immoral). If the Brexit/Trump post-truth age would only usher a greater encouragement for speculation or conjectures (Popper again), then Fuller’s book would be well-placed in the pantheon of intellectual pluralism; but if this endorsement obliterates the silly from the informed conjecture, then we are in trouble and the ensuing cacophony will turn us all deaf.

The second claim is at best supported by the likes of James Surowiecki (2004) who has argued that no matter how uninformed a crowd of people is, collectively it can guess the correct weight of a cow on stage (his TED talk). As folk wisdom, this is charming; as public policy, this is dangerous. Would you like a random group of people deciding how to store nuclear waste, and where? Would you subject yourself to the judgment of just any collection of people to decide on taking out your appendix or performing triple-bypass surgery?

When we turn to Trump, his supporters certainly like that he speaks his mind, just as Fuller says individuals should be granted the right to speak their minds (even if in error). But speaking one’s mind can also be a proxy for saying whatever, without filters, without critical thinking, or without thinking at all (let alone consulting experts whose very existence seems to upset Fuller). Since when did “speaking your mind” turn into scientific discourse? It’s one thing to encourage dissent and offer reasoned doubt and explore second opinions (as health care professionals and insurers expect), but it’s quite another to share your feelings and demand that they count as scientific authority.

Finally, even if we endorse the view that we “collectively” reach the truth, should we not ask: by what criteria? according to what procedure? under what guidelines? Herd mentality, as Nietzsche already warned us, is problematic at best and immoral at worst. Trump rallies harken back to the fascist ones we recall from Europe prior to and during WWII. Few today would entrust the collective judgment of those enthusiasts of the Thirties to carry the day.

Unlike Fuller’s sanguine posture, I shudder at the possibility that “in a post-truth world, this general line of thought is not merely endorsed but intensified.” This is neither because I worship experts and scorn folk knowledge nor because I have low regard for individuals and their (potentially informative) opinions. Just as we warn our students that simply having an opinion is not enough, that they need to substantiate it, offer data or logical evidence for it, and even know its origins and who promoted it before they made it their own, so I worry about uninformed (even if well-meaning) individuals (and presidents) whose gut will dictate public policy.

This way of unreasonably empowering individuals is dangerous for their own well-being (no paternalism here, just common sense) as well as for the community at large (too many untrained cooks will definitely spoil the broth). For those who doubt my concern, Trump offers ample evidence: trade wars with allies and foes that cost domestic jobs (when promising to bring jobs home), nuclear-war threats that resemble a game of chicken (as if no president before him ever faced such an option), and completely putting into disarray public policy procedures from immigration regulations to the relaxation of emission controls (that ignores the history of these policies and their failures).

Drought and suffering in Arbajahan, Kenya in 2006.
Photo by Brendan Cox and Oxfam International via Flickr / Creative Commons

 

Part Three: Post-Truth Revisited

There is something appealing, even seductive, in the provocation to doubt the truth as rendered by the (scientific) establishment, even as we worry about sowing the seeds of falsehood in the political domain. The history of science is the story of authoritative theories debunked, cherished ideas proven wrong, and claims of certainty falsified. Why not, then, jump on the “post-truth” wagon? Would we not unleash the collective imagination to improve our knowledge and the future of humanity?

One of the lessons of postmodernism (at least as told by Lyotard) is that “post-“ does not mean “after,” but rather, “concurrently,” as another way of thinking all along: just because something is labeled “post-“, as in the case of postsecularism, it doesn’t mean that one way of thinking or practicing has replaced another; it has only displaced it, and both alternatives are still there in broad daylight. Under the rubric of postsecularism, for example, we find religious practices thriving (80% of Americans believe in God, according to a 2018 Pew Research survey), while the number of unaffiliated, atheists, and agnostics is on the rise. Religionists and secularists live side by side, as they always have, more or less agonistically.

In the case of “post-truth,” it seems that one must choose between one orientation or another, or at least for Fuller, who claims to prefer the “post-truth world” to the allegedly hierarchical and submissive world of “truth,” where the dominant establishment shoves its truths down the throats of ignorant and repressed individuals. If post-truth meant, like postsecularism, the realization that truth and provisional or putative truth coexist and are continuously being re-examined, then no conflict would be at play. If Trump’s claims were juxtaposed to those of experts in their respective domains, we would have a lively, and hopefully intelligent, debate. False claims would be debunked, reasonable doubts could be raised, and legitimate concerns might be addressed. But Trump doesn’t consult anyone except his (post-truth) gut, and that is troublesome.

A Problematic Science and Technology Studies

Fuller admits that “STS can be fairly credited with having both routinized in its own research practice and set loose on the general public–if not outright invented—at least four common post-truth tropes”:

  1. Science is what results once a scientific paper is published, not what made it possible for the paper to be published, since the actual conduct of research is always open to multiple countervailing interpretations.
  2. What passes for the ‘truth’ in science is an institutionalised contingency, which if scientists are doing their job will be eventually overturned and replaced, not least because that may be the only way they can get ahead in their fields.
  3. Consensus is not a natural state in science but one that requires manufacture and maintenance, the work of which is easily underestimated because most of it occurs offstage in the peer review process.
  4. Key normative categories of science such as ‘competence’ and ‘expertise’ are moveable feasts, the terms of which are determined by the power dynamics that obtain between specific alignments of interested parties. (43)

In that sense, then, Fuller agrees that the positive lessons STS wished for the practice of the scientific community may have inadvertently found their way into a post-truth world that may abuse or exploit them in unintended ways. That is, something like “consensus” is challenged by STS because of how the scientific community pretends to get there knowing as it does that no such thing can ever be reached and when reached it may have been reached for the wrong reasons (leadership pressure, pharmaceutical funding of conferences and journals). But this can also go too far.

Just because consensus is difficult to reach (it doesn’t mean unanimity) and is susceptible to corruption or bias doesn’t mean that anything goes. Some experimental results are more acceptable than others and some data are more informative than others, and the struggle for agreement may take its political toll on the scientific community, but this need not result in silly ideas about cigarettes being good for our health or that obesity should be encouraged from early childhood.

It seems important to focus on Fuller’s conclusion because it encapsulates my concern with his version of post-truth, a condition he endorses not only in the epistemological plight of humanity but as an elixir with which to cure humanity’s ills:

While some have decried recent post-truth campaigns that resulted in victory for Brexit and Trump as ‘anti-intellectual’ populism, they are better seen as the growth pains of a maturing democratic intelligence, to which the experts will need to adjust over time. Emphasis in this book has been given to the prospect that the lines of intellectual descent that have characterised disciplinary knowledge formation in the academy might come to be seen as the last stand of a political economy based on rent-seeking. (130)

Here, we are not only afforded a moralizing sermon about (and it must be said, from) the academic privileged position, from whose heights all other positions are dismissed as anti-intellectual populism, but we are also entreated to consider the rantings of the know-nothings of the post-truth world as the “growing pains of a maturing democratic intelligence.” Only an apologist would characterize the Trump administration as mature, democratic, or intelligent. Where’s the evidence? What would possibly warrant such generosity?

It’s one thing to challenge “disciplinary knowledge formation” within the academy, and there are no doubt cases deserving reconsideration as to the conditions under which experts should be paid and by whom (“rent-seeking”); but how can these questions about higher education and the troubled relations between the university system and the state (and with the military-industrial complex) give cover to the Trump administration? Here is Fuller’s justification:

One need not pronounce on the specific fates of, say, Brexit or Trump to see that the post-truth condition is here to stay. The post-truth disrespect for established authority is ultimately offset by its conceptual openness to previously ignored people and their ideas. They are encouraged to come to the fore and prove themselves on this expanded field of play. (Ibid)

This, too, is a logical stretch: is disrespect for the authority of the establishment the same as, or does it logically lead to, the “conceptual” openness to previously “ignored people and their ideas”? This is not a claim on behalf of the disenfranchised. Perhaps their ideas were simply bad or outright racist or misogynist (as we see with Trump). Perhaps they were ignored because there was hope that they would change for the better, become more enlightened, not act on their white supremacist prejudices. Should we have “encouraged” explicit anti-Semitism while we were at it?

Limits to Tolerance

We tolerate ignorance because we believe in education and hope to overcome some of it; we tolerate falsehood in the name of eventual correction. But we should never tolerate offensive ideas and beliefs that are harmful to others. Once again, it is one thing to argue about black holes, and quite another to argue about whether black lives matter. It seems reasonable, as Fuller concludes, to say that “In a post-truth utopia, both truth and error are democratised.” It is also reasonable to say that “You will neither be allowed to rest on your laurels nor rest in peace. You will always be forced to have another chance.”

But the conclusion that “Perhaps this is why some people still prefer to play the game of truth, no matter who sets the rules” (130) does not follow. Those who “play the game of truth” are always vigilant about falsehoods and post-truth claims, and to say that they are simply dupes of those in power is both incorrect and dismissive. On the contrary: Socrates was searching for the truth and fought with the sophists, as Popper fought with the logical positivists and the Kuhnians, and as scientists today are searching for the truth and continue to fight superstitions and debunked pseudoscience about vaccination causing autism in young kids.

If post-truth is like postsecularism, scientific and political discourses can inform each other. When power-plays by ignoramus leaders like Trump are obvious, they could shed light on less obvious cases of big pharma leaders or those in charge of the EPA today. In these contexts, inconvenient facts and truths should prevail and the gamesmanship of post-truthers should be exposed for what motivates it.

Contact details: rsassowe@uccs.edu

* Special thanks to Dr. Denise Davis of Brown University, whose contribution to my critical thinking about this topic has been profound.

References

Theodor W. Adorno (1998/1963), Critical Models: Interventions and Catchwords. Translated by Henry W. Pickford. New York: Columbia University Press

Kurt Andersen (2017), Fantasyland: How America Went Hotwire: A 500-Year History. New York: Random House

Monya Baker, “1,500 scientists lift the lid on reproducibility,” Nature Vol. 533, Issue 7604, 5/26/16 (corrected 7/28/16)

Michael Bowker (2003), Fatal Deception: The Untold Story of Asbestos. New York: Rodale.

Robert Darnton, “The Greatest Show on Earth,” New York Review of Books Vo. LXV, No. 11 6/28/18, pp. 68-72.

Al Gore (2006), An Inconvenient Truth: The Planetary Emergency of Global Warming and What Can Be Done About It. New York: Rodale.

Richard Hofstadter (1962), Anti-Intellectualism in American Life. New York: Vintage Books.

Jean- François Lyotard (1984), The Postmodern Condition: A Report on Knowledge. Translated by Geoff Bennington and Brian Massumi. Minneapolis: University of Minnesota Press.

Robert K. Merton (1973/1942), “The Normative Structure of Science,” The Sociology of Science: Theoretical and Empirical Investigations. Chicago and London: The University of Chicago Press, pp. 267-278.

Hans E. Plesser, “Reproducibility vs. Replicability: A Brief History of Confused Terminology,” Frontiers in Neuroinformatics, 2017; 11: 76; online: 1/18/18.

Robert N. Proctor (1995), Cancer Wars: How Politics Shapes What We Know and Don’t Know About Cancer. New York: Basic Books.

James Surowiecki (2004), The Wisdom of Crowds. New York: Anchor Books.

Author Information: Moti Mizrahi, Florida Institute of Technology, mmizrahi@fit.edu

Mizrahi, Moti. “The (Lack of) Evidence for the Kuhnian Image of Science.” Social Epistemology Review and Reply Collective 7, no. 7 (2018): 19-24.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-3Z5

See also:

Image by Narcis Sava via Flickr / Creative Commons

 

Whenever the work of an influential philosopher is criticized, a common move made by those who seek to defend the influential philosopher’s work is to claim that his or her ideas have been misconstrued. This is an effective move, of course, for it means that the critics have criticized a straw man, not the ideas actually put forth by the influential philosopher. However, this move can easily backfire, too.

For continued iterations of this move could render the ideas in question immune to criticism in a rather ad hoc fashion. That is to say, shouting “straw man” every time an influential philosopher’s ideas are subjected to scrutiny is rather like shouting “wolf” when none is around; it could be seen as an attempt to draw attention to that which may not be worthy of attention.

The question, then, is whether the influential philosopher’s ideas are worthy of attention and/or acceptance. In particular, are Kuhn’s ideas about scientific revolutions and incommensurability worthy of acceptance? As I have argued, along with a few other contributors to my edited volume, The Kuhnian Image of Science: Time for a Decisive Transformation? (2018), they may not be because they are based on dubious assumptions and fallacious argumentation.

In their reviews of The Kuhnian Image of Science: Time for a Decisive Transformation? (2018), both Markus Arnold (2018) and Amanda Bryant (2018) complain that the contributors who criticize Kuhn’s theory of scientific change have misconstrued his philosophy of science and they praise those who seek to defend the Kuhnian image of science. In what follows, then, I would like to address their claims about misconstruing Kuhn’s theory of scientific change. But my focus here, as in the book, will be the evidence (or lack thereof) for the Kuhnian image of science. I will begin with Arnold’s review and then move on to Bryant’s review.

Arnold on the Evidence for the Kuhnian Image of Science

Arnold (2018, 42) states that “one of the results of [his] review” is that “the ‘inductive reasoning’ intended to refute Kuhn’s incommensurability thesis (found in the first part of the book) is actually its weakest part.” I am not sure what he means by that exactly. First, I am not sure in what sense inductive reasoning can be said to refute a thesis, given that inductive arguments are the sort of arguments whose premises do not necessitate the truth of their conclusions, whereas a refutation of p, if sound, supposedly shows that p must be false.

Second, contrary to what Arnold claims, I do not think that the chapters in Part I of the book contain “‘inductive reasoning’ intended to refute Kuhn’s incommensurability thesis” (Arnold 2018, 42). Speaking of my chapter in particular, Chapter 1 (Mizrahi 2018b, 32-38), it contains two arguments intended to show that there is no deductive support for the Kuhnian thesis of taxonomic incommensurability (Mizrahi 2018b, 32), and an argument intended to show that there is no inductive support for the Kuhnian thesis of taxonomic incommensurability (Mizrahi 2018b, 37).

These arguments are deductive, not inductive, for their premises, if true, guarantee the truth of their conclusions. Besides, to argue that there is no evidence for p is not the same as arguing that p is false. None of my arguments is intended to show that p (namely, the Kuhnian thesis of taxonomic incommensurability) is false.

Rather, my arguments show that there is no evidence for p (namely, the Kuhnian thesis of taxonomic incommensurability). For these reasons, as a criticism of Part I of the book, Arnold’s (2018, 42) claim that “the ‘inductive reasoning’ intended to refute Kuhn’s incommensurability thesis (found in the first part of the book) is actually its weakest part” completely misses the mark.

Moreover, the only thing I could find in Arnold’s review that could be construed as support for this claim is the aforementioned complaint about straw-manning Kuhn. As Arnold (2018, 43) puts it, “the counter-arguments under consideration brought forward against his model seem, paradoxically, to underestimate the complexity of Kuhn’s claims.”

In other words, Kuhn’s theory of scientific change is so complex and those who attempt to criticize it fail to appreciate its complexity. But why? Why do the criticisms fail to appreciate the complexity of Kuhn’s theory? How complex is it such that it defies interpretation and criticism? Arnold does not say. Instead, he (Arnold 2018, 43) states that “it is not clear, why Kuhn’s ‘image of science’ should be dismissed because […] taxonomic incommensurability ‘is the exception rather than the rule’ [Mizrahi 2018b,] (38).”

As I argue in Chapter 1, however, the fact that taxonomic incommensurability “is the exception rather than the rule” (Mizrahi 2018b, 38) means that Kuhn’s theory of scientific change is a bad theory because it shows that Kuhn’s theory has neither explanatory nor predictive power. A “theory” with no explanatory and/or predictive power is no theory at all (Mizrahi 2018b, 37-38). From his review, however, it is clear that Arnold thinks of Kuhn’s image of science as a theory of scientific change.

For instance, he talks about “Kuhn’s epistemology” (Arnold 2018, 45), “Kuhn’s theory of incommensurability” (Arnold 2018, 46), and Kuhn’s “complex theory of science” (Arnold 2018, 42). If Kuhn’s thesis of taxonomic incommensurability has no explanatory and/or predictive power, then it is a bad theory, perhaps not even a theory at all, let alone a general theory of scientific knowledge or scientific change.

In that respect, I found it rather curious that, on the one hand, Arnold approves of Alexandra Argamakova’s (2018) criticism of the universal ambitions of Kuhn’s image of science, but on the other hand, he wants to attribute to Kuhn the view that “scientific revolutions are rare” (Arnold 2018, 43). Arnold quotes with approval Argamakova’s (2018, 54) claim that “distinct breakthroughs in science can be marked as revolutions, but no universal system of criteria for such appraisal can be formulated in a normative philosophical manner” (emphasis added).

In other words, if Argamakova is right, then there can be no philosophical theory of scientific change in general, Kuhnian or otherwise. So Arnold cannot be in agreement with Argamakova without thereby abandoning the claim that Kuhn’s image of science is an “epistemology” (Arnold 2018, 45) of scientific knowledge or a “complex theory of science” (Arnold 2018, 42).

Arnold (2018, 45) also asserts that “the allegation that Kuhn developed his theory on the basis of selected historical cases is refuted” by Kindi (2018). Even if that were true, it would mean that Kuhn’s theory has no inductive support, as I argue in Chapter 1 of the book (Mizrahi 2018b, 32-38). So I am not sure how this point is supposed to help Arnold in defending the Kuhnian image of science. For if there is no inductive support for the Kuhnian image of science, as Arnold seems to think, and there is no deductive support either, as I (Mizrahi 2018b, 25-44) and Park (2018, 61-74) argue, then what evidence is there for the Kuhnian image of science?

For present purposes, the important point is not how Kuhn “developed his theory” (Arnold 2018, 45) but rather what supports his theory of scientific change. What is the evidence for a Kuhnian theory of scientific change? If I am right (Mizrahi 2018b), or if Park (2018) is right, then there is neither deductive support nor inductive support for a Kuhnian theory of scientific change. If Argamakova is right, then there can be no general theory of scientific change at all, Kuhnian or otherwise.

It is also important to note here that Arnold (2018, 45) praises both Kindi (2018) and Patton (2018) for offering “a close reading of Kuhn’s work,” but he does not mention that they offer incompatible interpretations of that work, specifically, of the evidence for Kuhn’s ideas about scientific change. On Kindi’s reading of Kuhn, the argument for the Kuhnian image of science is a deductive argument from first principles, whereas on Patton’s reading of Kuhn, the argument for the Kuhnian image of science is an inference to the best explanation (see Patton 2015, cf. Mizrahi 2018a, 12-13; Mizrahi 2015, 51-53).

Bryant on the Evidence for the Kuhnian Image of Science

Like Arnold, Bryant (2018, 1) wonders whether Kuhn’s views on scientific change can be pinned down and criticized or perhaps there are many “Thomases Kuhn.” Again, I think we do not want to make Kuhn’s views too vague and/or ambiguous (Argamakova 2018, 47-50), and thus immune to criticism in a rather ad hoc fashion. For that, in addition to being based on dubious assumptions and fallacious argumentation, would be another reason to think that Kuhn’s views are not worthy of acceptance.

Bryant (2018, 1) also wonders “whether the so-called Kuhnian image of science is really so broadly endorsed as to be the potential subject of (echoing Kuhn’s own phrase) a ‘decisive transformation’.” As I see it, however, the question is not whether the Kuhnian image of science is “broadly endorsed.” Rather, the question is whether “we are now possessed” by it. When Kuhn wrote that (in)famous first line of the introduction to The Structure of Scientific Revolutions, the image of science by which we were possessed was a positivist image of science according to which science develops “by the accumulation of individual discoveries and inventions” (Kuhn 1962/1996, 2). Arguably, philosophers of science were never possessed by such a positivist image of science as much as they are possessed by the Kuhnian image of science.

This is evidenced by the fact that no positivist work in philosophy of science has had as much impact as Kuhn’s seminal work (Mizrahi 2018a, 1-2). Accordingly, even if the Kuhnian image of science is not “broadly endorsed,” it is quite clear that philosophers of science are possessed by it. For this reason, an “exorcism,” or a “decisive transformation,” is required in order to rid ourselves of this image of science. And what better way to do so than by showing that it is based on dubious assumptions and fallacious argumentation.

As far as the evidence (or lack thereof) for the Kuhnian image of science, Bryant (2018, 2) claims that “Case studies can be interesting, informative, and evidential” (emphasis added). I grant that case studies can be interesting and informative, but I doubt that they can be evidential. From “Scientific episode E has property F,” it does not follow that F is a characteristic of scientific episodes in general. As far as Kuhn is concerned, it is clear that he used just a few case studies (e.g., the phlogiston case) in support of his ideas about scientific change and incommensurability.

The problem with that, as I argue in Chapter 1 of the book (Mizrahi 2018b, 32-38), is that no general theory of scientific change can be derived from a few cherry-picked case studies. Even if we grant that the phlogiston case is a genuine case of a so-called “Kuhnian revolution” and taxonomic incommensurability, despite the fact that there are rebutting defeaters (Mizrahi 2018b, 33-36), no general conclusions about the nature of science can be drawn from one (or even a few) such cases (Mizrahi 2018b, 36-37).

From the fact that one (or a few) cherry-picked episode(s) from the history of science exhibits a particular property, it does not follow that all scientific episodes have that property; otherwise, from the “Piltdown man” episode we would have to conclude that fraud characterizes scientific discovery in general (Mizrahi 2018b, 37-38).

Speaking of scientific discovery, Bryant (2018, 2) takes issue with the fact that I cite “just two authors, Eric Oberheim and Paul Hoyningen-Huene, who use the language of discovery to characterize incommensurability.” For Bryant (2018, 2), this suggests that “it isn’t clear that the assumption Mizrahi takes pains to reject is particularly widespread” (emphasis added). I suppose that “the assumption” in question here is that Kuhn “discovered” incommensurability.

If so, then I would like to clarify that I mention the fact that Oberheim and Hoyningen-Huene talk about incommensurability in terms of discovery, and claim that Kuhn “discovered” it, not to argue against it (i.e., to argue that Kuhn did not discover incommensurability), but rather to show that some of the elements of the Kuhnian image of science, such as incommensurability, are sometimes taken for granted. When it is said that someone has discovered something, it gives the impression that what has been discovered is a fact, and so no arguments are needed.

When it comes to incommensurability, however, it is far from clear that it is a fact about scientific change, and so good arguments are needed in order to establish that episodes of scientific change exhibit taxonomic incommensurability. If I am right, or if Park (2018) and Sankey (2018) are right, then there are no good arguments that establish this.

Not Conclusions, But Questions

In light of the above, I think that the questions raised in the edited volume under review remain urgent (cf. Rehg 2018). Are there good reasons or compelling evidence for the Kuhnian model of theory change in science? If there are no good reasons or compelling evidence for such a model, as I (Mizrahi 2018b), Park (2018), and Sankey (2018) argue, what’s next for philosophers of science? Should we abandon the search for a general theory of science, as Argamakova (2018) suggests? Are there better models of scientific change? Perhaps evolutionary (Marcum 2018) or orthogenetic (Renzi and Napolitano 2018) models?

• • •

I would like to thank Markus Arnold and Amanda Bryant for their thoughtful reviews. I am also grateful to Adam Riggio and Eric Kerr for organizing this book symposium and for inviting me to participate.

Contact details: mmizrahi@fit.edu

References

Argamakova, Alexandra. “Modeling Scientific Development: Lessons from Thomas Kuhn.” In The Kuhnian Image of Science: Time for a Decisive Transformation?, edited by Moti Mizrahi, 45-59. London: Rowman & Littlefield, 2018.

Arnold, Markus. “Is There Anything Wrong With Thomas Kuhn?” Social Epistemology Review and Reply Collective 7, no. 5 (2018): 42-47.

Bryant, Amanda. “Each Kuhn Mutually Incommensurable.” Social Epistemology Review and Reply Collective 7, no. 6 (2018): 1-7.

Kindi, Vasso. “The Kuhnian Straw Man.” In The Kuhnian Image of Science: Time for a Decisive Transformation?, edited by Moti Mizrahi, 95-112. London: Rowman & Littlefield, 2018.

Kuhn, Thomas S. The Structure of Scientific Revolutions. Third Edition. Chicago: The University of Chicago Press, 1962/1996.

Marcum, James A. “Revolution or Evolution in Science? A Role for the Incommensurability Thesis?” In The Kuhnian Image of Science: Time for a Decisive Transformation?, edited by Moti Mizrahi, 155-173. London: Rowman & Littlefield, 2018.

Mizrahi, Moti. “A Reply to Patton’s ‘Incommensurability and the Bonfire of the Meta-Theories.” Social Epistemology Review and Reply Collective 4, no. 10 (2015): 51-53.

Mizrahi, Moti. “Introduction.” In The Kuhnian Image of Science: Time for a Decisive Transformation?, edited by Moti Mizrahi, 1-22. London: Rowman & Littlefield, 2018a.

Mizrahi, Moti. “Kuhn’s Incommensurability Thesis: What’s the Argument?” In The Kuhnian Image of Science: Time for a Decisive Transformation?, edited by Moti Mizrahi, 25-44. London: Rowman & Littlefield, 2018b.

Park, Seungbae. “Can Kuhn’s Taxonomic Incommensurability be an Image of Science?” In The Kuhnian Image of Science: Time for a Decisive Transformation?, edited by Moti Mizrahi, 61-74. London: Rowman & Littlefield, 2018.

Patton, Lydia. “Incommensurability and the Bonfire of the Meta-Theories: Response to Mizrahi.” Social Epistemology Review and Reply Collective 4, no. 7 (2015): 51-58.

Patton, Lydia. “Kuhn, Pedagogy, and Practice: A Local Reading of Structure.” In The Kuhnian Image of Science: Time for a Decisive Transformation?, edited by Moti Mizrahi, 113-130. London: Rowman & Littlefield, 2018.

Rehg, William. “Kuhn’s Image of Science.” Metascience (2018): https://doi.org/10.1007/s11016-018-0306-2.

Renzi, Barbara G. and Giulio Napolitano. “The Biological Metaphors of Scientific Change.” In The Kuhnian Image of Science: Time for a Decisive Transformation?, edited by Moti Mizrahi, 177-190. London: Rowman & Littlefield, 2018.

Author Information: James A. Marcum, Baylor University, james_marcum@baylor.edu

Marcum, James A. “A Role for Taxonomic Incommensurability in Evolutionary Philosophy of Science.” Social Epistemology Review and Reply Collective 7, no. 7 (2018): 9-14.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-3YP

See also:

Image by Sanofi Pasteur via Flickr / Creative Commons

 

In a review of my chapter (Marcum 2018), Amanda Bryant (2018) charges me with failing to discuss the explanatory role taxonomic incommensurability (TI) plays in my revision of Kuhn’s evolutionary philosophy of science. To quote Bryant at length,

One of Marcum’s central aims is to show that incommensurability plays a key explanatory role in a refined version of Kuhn’s evolutionary image of science. The role of incommensurability on this view is to account for scientific speciation. However, Marcum shows only that we can characterize scientific speciation in terms of incommensurability, without clearly establishing the explanatory payoff of so doing. He does not succeed in showing that incommensurability has a particularly enriching explanatory role, much less that incommensurability is “critical for conceptual evolution within the sciences” or “an essential component of…the growth of science” (168).

Bryant is right. I failed to discuss the explanatory role of TI for the three historical case studies, as listed in Table 8.1, in section 5, “Revising Kuhn’s Evolutionary Image of Science and Incommensurability,” of my chapter. Obviously, my aim in this response, then, is to amend that failure by discussing TI’s role in the case studies and by revising the chapter’s Table to include TI.

Before discussing the role of TI in the historical case studies, I first develop the notion of TI in terms of Kuhn’s revision of the original incommensurability thesis. Kuhn (1983) responded to critics of the original thesis in a symposium paper delivered at the 1982 biannual meeting of the Philosophy of Science Association.

In the paper, Kuhn admitted that his primary intention for incommensurability was more “modest” than with what critics had charged him. Rather than radical or universal changes in terms and concepts—what is often called “global” incommensurability (Hoyningen-Huene 2005, Marcum 2015, Simmons 1994)—Kuhn claimed that only a handful of terms and concepts are incommensurable after a paradigm shift. He called this thesis “local” incommensurability.

More Common Than Incommensurable

Kuhn’s revision of the original incommensurability thesis has important implications for the TI thesis. To that end, I propose three types of TI. The first is comparable to Kuhn’s local incommensurability in which only a small number of terms and concepts are incommensurable, between the lexicons of two scientific specialties. The second is akin to global incommensurability in which two lexicons are radically and universally incommensurable with one another—sharing only a few commensurable terms and concepts.

An example of this type of incommensurability is the construction of a drastically new lexicon accompanying the evolution of a specialty. Both local and global TI represent, then, two poles along a continuum. For the type of TI falling along this continuum, I propose the notion of regional TI—in keeping with the geographical metaphor.

Unfortunately, sharper delineation among the three types of TI in terms of the quantity and quality of incommensurable and commensurable terms and concepts composing taxonomically incommensurable lexicons cannot be made currently, other than local TI comprises one end of the continuum while global TI the other end, with regional TI occupying an intermediate position between them. Notwithstanding this imprecise delineation, the three types of TI are apt for explaining the evolution of the microbiological specialties of bacteriology, virology, and retrovirology, especially with respect to their tempos and modes.

Revised Table. Types of tempo, mode, and taxonomic incommensurability for the evolution of microbiological specialties of bacteriology, virology, and retrovirology (see text for details).

Scientific Specialty Tempo Mode Taxonomic

Incommensurability

 

Bacteriology Bradytelic Phyletic Global

 

Virology Tachytelic Quantal Regional

 

Retrovirology Horotelic Speciation Local

 

 

Examples Bacterial and Viral

As depicted in the Revised Table, the evolution of bacteriology, with its bradytelic tempo and phyletic mode, is best accounted for through global TI. A large number of novel incommensurable terms and concepts appeared with the evolution of bacteriology and the germ theory of disease, and global TI afforded the bacteriology lexicon the conceptual space to evolve fully and independently by isolating that lexicon from both botany and zoology lexicons, as well as from other specialty lexicons in microbiology.

For example, in terms of microbiology as a specialty separate from botany and zoology, bacteria are prokaryotes compared to other microorganisms such as algae, fungi, and protozoa, which are eukaryotes. Eukaryotes have a nucleus surrounded by a plasma membrane that separates the chromosomes from the cytoplasm, while prokaryotes do not. Rather, prokaryotes like bacteria have a single circular chromosome located in the nucleoid region of the cell.

However, the bacteriology lexicon does share a few commensurable terms and concepts with the lexicons of other microbiologic specialties and with the cell biology lexicons of botany and zoology. For example, both prokaryotic and eukaryotic cells contain a plasma membrane that separates the cell’s interior from the external environment. Examples of many other incommensurable (and of a few commensurable) terms and concepts make up the lexicons of these specialties but suffice these examples to provide how global TI provided the bacteriology lexicon a cognitive environment so that it could evolve as a distinct specialty.

Also, as depicted in the Revised Table, the evolution of virology, with its tachytelic tempo and quantal mode, is best accounted for through regional TI. A relatively smaller number of new incommensurable terms and concepts appeared with the evolution of virology compared to the evolution of bacteriology, and regional TI afforded the virology lexicon the conceptual space to evolve freely and self-sufficiently by isolating that lexicon from the bacteriology lexicon, as well as from other biology lexicons.

For example, the genome of the virus is surrounded by a capsid or protein shell, which distinguishes it from both prokaryotes and eukaryotes—neither of which have such a structure. Moreover, viruses do not have a constitutive plasma membrane, although some viruses acquire a plasma membrane from the host cell when exiting it during lysis. However, the function of the viral plasma membrane is different from that for both prokaryotes and eukaryotes.

Interestingly, the term plasma membrane for the virology lexicon is both commensurable and incommensurable, when compared to other biology lexicons. The viral plasma membrane is commensurable in that it is comparable in structure to the plasma membrane of prokaryotes and eukaryotes but it is incommensurable in that it functions differently. Finally, some viral genomes are composed of DNA similar to prokaryotic and eukaryotic genomes while others are composed of RNA; and, it is this RNA genome that led to the evolution of the retrovirology specialty.

Image by AJC1 via Flickr / Creative Commons

And As Seen in the Retrovirological

As depicted lastly in the Revised Table, the evolution of retrovirology, with its horotelic tempo and speciation mode, is best accounted for through local TI. An even smaller number of novel incommensurable terms and concepts accompanied the evolution of retrovirology as compared to the number of novel incommensurable terms and concepts involved in the evolution of the virology lexicon vis-à-vis the bacteriology lexicon.

And, as true for the role of TI in the evolution of bacteriology and virology, local TI afforded the retrovirology lexicon the conceptual space to evolve rather autonomously by isolating that lexicon from the virology and bacteriology lexicons. For example, retroviruses, as noted previously, contain only an RNA genome but the replication of the retrovirus and its genome does not involve replication of the RNA genome from the RNA directly, as for other RNA viruses.

Rather, retrovirus replication involves the formation of a DNA provirus through the enzyme reverse transcriptase. The DNA provirus is subsequently incorporated into the host’s genome, where it remains dormant until replication of the retrovirus is triggered.

The incommensurability associated with retrovirology evolution is local since only a few incommensurable terms and concepts separate the virology and retrovirology lexicons. But that incommensurability was critical for the evolution of the retrovirology specialty (although given how few incommensurable terms and concepts exist between the virology and retrovirology lexicons, a case could be made for retrovirology representing a subspecialty of virology).

Where the Payoff Lies

In her review, Bryant makes a distinction, as quoted above, between characterizing the evolution of the microbiological specialties via TI and explaining their evolution via TI. In terms of the first distinction, TI is the product of the evolution of a specialty and its lexicon. In other words, when reconstructing historically the evolution of a specialty, the evolutionary outcome is a new specialty and its lexicon—which is incommensurable locally, regionally, or globally with respect to other specialty lexicons.

For example, the retrovirology lexicon—when compared to the virology lexicon—has few incommensurable terms, such as DNA provirus and reverse transcriptase. The second distinction involves the process or mechanism by which the evolution of the specialty’s lexicon takes place vis-à-vis TI. In other words, TI plays a critical role in the evolutionary process of a specialty and its lexicon.

Keeping with the retrovirology example, the experimental result that actinomysin D inhibits Rous sarcoma virus was an important anomaly with respect to the virology lexicon, which could only explain the replication of RNA viruses in terms of the Central Dogma’s flow of genetic information. TI, then, represents the mechanism, i.e. by providing the conceptual space, for the evolution of a new specialty with respect to incommensurable terms and concepts.

In conclusion, the “explanatory payoff” for TI with respect to the revised Kuhnian evolutionary philosophy of science is that such incommensurability provides isolation for a scientific specialty and its lexicon so that it can evolve from a parental stock. For, without the conceptual isolation to develop its lexicon, a specialty cannot evolve.

Just as biological species like Darwin’s Galápagos finches, for instance, required physical isolation from one another to evolve (Lack 1983), so the evolving microbiological specialties also required conceptual isolation from one another and from other biology specialties and their lexicons. TI accounts for or explains the evolution of science and its specialties in terms of providing the necessary conceptual opportunity for the specialties to emerge and then to evolve.

Moreover, it is of interest to note that an apparent relationship exists between the various tempos and modes and the different types of TI. For example, the retrovirology case study suggests that local TI is commonly associated with a horotelic tempo and speciation mode—which to some extent makes sense intuitively. In other words, speciation requires far fewer lexical changes than phylogeny, which requires many more lexical changes or an almost completely new lexicon—as the evolution of bacteriology illustrates.

The proposed evolutionary philosophy of science, then, accounts for the emergence of bacteriology in terms of a specific tempo and mode, as well as a particular type of TI; and, it thereby provides a rich explanation for its emergence. Furthermore, the quantity and quality of taxonomically incommensurable terms and concepts involved in the evolution of the microbiology specialties suggest the following relative frequency for the different types of TI: local TI > regional RI > global TI.

The Potential of Evolutionary Paradigms

Finally, I proposed in my chapter that Kuhn’s revised evolutionary philosophy of science is a good candidate for a general philosophy of science, even in light of philosophy of science’s current pluralistic or perspectival stance. Interestingly, regardless of the increasing specialization within the natural sciences (Wray 2005), these sciences are moving towards integration in order to tackle complex natural phenomena. For example, cancer is simply too complex a disease to succumb to a single specialty (Williams 2015).

The revised Kuhnian evolutionary philosophy of science helps to appreciate and account for the drive and need for integration of different scientific specialties to investigate complex natural phenomena, such as cancer. Specifically, one of the important reasons for the integration is that no single scientist can master the necessary lexicons, whether biochemistry, bioinformatics, cell biology, genomic biology, immunology, molecular biology, physiology, etc., needed to investigate and eventually to cure the disease. A scientist might be bilingual or even trilingual with respect to specialties but certainly not multilingual.

The conceptual and methodological approach, which integrates these various specialties, stands a better chance in discovering the pathological mechanisms involved in carcinogenesis and thereby in developing effective therapies. Integrated science, then, requires a systems or network approach since no one scientists can master the various specialties needed to investigate a complex natural phenomenon.

In the end, TI helps to make sense of why integrated science is important for the future evolution of science and of how an evolutionary philosophy of science can function as a general philosophy of science.

Contact details: james_marcum@baylor.edu

References

Bryant, Amanda. “Each Kuhn Mutually Incommensurable”, Social Epistemology Review and Reply Collective 7, no. 6 (2018): 1-7.

Hoyningen-Huene, Paul. “Three Biographies: Kuhn, Feyerabend, and Incommensurability”, In Rhetoric and Incommensurability. Randy A. Harris (ed.), West Lafayette, IN: Parlor Press, (2005): 150-175.

Kuhn, Thomas S. “Commensurability, Comparability, Communicability”, PSA: 1982, no. 2

(1983): 669-688.

Lack, David. Darwin’s Finches. Cambridge: Cambridge University Press, (1983).

Marcum, James A. Thomas Kuhn’s Revolutions: A Historical and an Evolutionary Philosophy of Science. London: Bloomsbury, (2015).

Marcum, James A. “Revolution or Evolution in Science?: A Role for the Incommensurability Thesis?”, In The Kuhnian Image of Science: Time for a Decisive Transformation? Moti Mizrahi (ed.), Lanham, MD: Rowman & Littlefield, (2018): 155-173.

Simmons, Lance. “Three Kinds of Incommensurability Thesis”, American Philosophical Quarterly 31, no. 2 (1994): 119-131.

Williams, Sarah C.P. “News Feature: Capturing Cancer’s Complexity”, Proceedings of the National Academy of Sciences, 112, no. 15 (2015): 4509-4511.

Wray, K. Brad. “Rethinking Scientific Specialization”, Social Studies of Science 35. no. 1 (2005): 151-164.

Author Information: Seungbae Park, Ulsan National Institute of Science and Technology, nature@unist.ac.kr

Park, Seungbae. “Philosophers and Scientists are Social Epistemic Agents.” Social Epistemology Review and Reply Collective 7, no. 6 (2018): 31-40.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-3Yo

Please refer to:

The example is from the regime of Hosni Mubarak, but these were the best photos the Digital Editor could find in Creative Commons when he was uploading the piece.

The style of examples common to epistemology, whether social or not, are often innocuous, ordinary situation. But the most critical uses and misuses of knowledge and belief remain all-too-ordinary situations already. If scepticism about our powers to know and believe hold – or are at least held sufficiently – then the most desperate political prisoner has lost her last glimmer of hope. Truth.
Image by Hossam el-Hamalawy via Flickr / Creative Commons

 

In this paper, I reply to Markus Arnold’s comment and Amanda Bryant’s comment on my work “Can Kuhn’s Taxonomic Incommensurability be an Image of Science?” in Moti Mizrahi’s edited collection, The Kuhnian Image of Science: Time for a Decisive Transformation?.

Arnold argues that there is a gap between the editor’s expressed goal and the actual content of the book. Mizrahi states in the introduction that his book aims to increase “our understanding of science as a social, epistemic endeavor” (2018: 7). Arnold objects that it is “not obvious how the strong emphasis on discounting Kuhn’s incommensurability thesis in the first part of the book should lead to a better understanding of science as a social practice” (2018: 46). The first part of the volume includes my work. Admittedly, my work does not explicitly and directly state how it increases our understanding of science as a social enterprise.

Knowledge and Agreement

According to Arnold, an important meaning of incommensurability is “the decision after a long and futile debate to end any further communication as a waste of time since no agreement can be reached,” and it is this “meaning, describing a social phenomenon, which is very common in science” (Arnold, 2018: 46). Arnold has in mind Kuhn’s claim that a scientific revolution is completed not when opposing parties reach an agreement through rational argumentations but when the advocates of the old paradigm die of old age, which means that they do not give up on their paradigm until they die.

I previously argued that given that most recent past paradigms coincide with present paradigms, most present paradigms will also coincide with future paradigms, and hence “taxonomic incommensurability will rarely arise in the future, as it has rarely arisen in the recent past” (Park, 2018: 70). My argument entails that scientists’ decision to end further communications with their opponents has been and will be rare, i.e., such a social phenomenon has been and will be rare.

On my account, the opposite social phenomenon has been and will rather be very common, viz., scientists keep communicating with each other to reach an agreement. Thus, my previous contention about the frequency of scientific revolutions increases our understanding of science as a social enterprise.

Let me now turn to Bryant’s comment on my criticism against Thomas Kuhn’s philosophy of science. Kuhn (1962/1970, 172–173) draws an analogy between the development of science and the evolution of organisms. According to evolutionary theory, organisms do not evolve towards a goal. Similarly, Kuhn argues, science does not develop towards truths. The kinetic theory of heat, for example, is no closer to the truth than the caloric theory of heat is, just as we are no closer to some evolutionary goal than our ancestors were. He claims that this analogy is “very nearly perfect” (1962/1970, 172).

My objection (2018a: 64–66) was that it is self-defeating for Kuhn to use evolutionary theory to justify his philosophical claim about the development of science that present paradigms will be replaced by incommensurable future paradigms. His philosophical view entails that evolutionary theory will be superseded by an incommensurable alternative, and hence evolutionary theory is not trustworthy. Since his philosophical view relies on this untrustworthy theory, it is also untrustworthy, i.e., we ought to reject his philosophical view that present paradigms will be displaced by incommensurable future paradigms.

Bryant replies that “Kuhn could adopt the language of a paradigm (for the purposes of drawing an analogy, no less!) without committing to the literal truth of that paradigm” (2018: 3). On her account, Kuhn could have used the language of evolutionary theory without believing that evolutionary theory is true.

Can We Speak a Truth Without Having to Believe It True?

Bryant’s defense of Kuhn’s position is brilliant. Kuhn would have responded exactly as she has, if he had been exposed to my criticism above. In fact, it is a common view among many philosophers of science that we can adopt the language of a scientific theory without committing to the truth of it.

Bas van Fraassen, for example, states that “acceptance of a theory involves as belief only that it is empirically adequate” (1980: 12). He also states that if “the acceptance is at all strong, it is exhibited in the person’s assumption of the role of explainer” (1980: 12). These sentences indicate that according to van Fraassen, we can invoke a scientific theory for the purpose of explaining phenomena without committing to the truth of it. Rasmus Winther (2009: 376), Gregory Dawes (2013: 68), and Finnur Dellsén (2016: 11) agree with van Fraassen on this account.

I have been pondering this issue for the past several years. The more I reflect upon it, however, the more I am convinced that it is problematic to use the language of a scientific theory without committing to the truth of it. This thesis would be provocative and objectionable to many philosophers, especially to scientific antirealists. So I invite them to consider the following two thought experiments.

First, imagine that an atheist uses the language of Christianity without committing to the truth of it (Park, 2015: 227, 2017a: 60). He is a televangelist, saying on TV, “If you worship God, you’ll go to heaven.” He converts millions of TV viewers into Christianity. As a result, his church flourishes, and he makes millions of dollars a year. To his surprise, however, his followers discover that he is an atheist.

They request him to explain how he could speak as if he were a Christian when he is an atheist. He replies that he can use the language of Christianity without believing that it conveys truths, just as scientific antirealists can use the language of a scientific theory without believing that it conveys the truth.

Second, imagine that scientific realists, who believe that our best scientific theories are true, adopts Kuhn’s philosophical language without committing to Kuhn’s view of science. They say, as Kuhn does, “Successive paradigms are incommensurable, so present and future scientists would not be able to communicate with each other.” Kuhn requests them to explain how they could speak as if they were Kuhnians when they are not Kuhnians. They reply that they can adopt his philosophical language without committing to his view of science, just as scientific antirealists can adopt the language of a scientific theory without committing to the truth of it.

The foregoing two thought experiments are intended to be reductio ad absurdum. That is, my reasoning is that if it is reasonable for scientific antirealists to speak the language of a scientific theory without committing to the truth of it, it should also be reasonable for the atheist to speak the language of Christianity and for scientific realists to speak Kuhn’s philosophical language. It is, however, unreasonable for them to do so.

Let me now diagnose the problems with the atheist’s speech acts and scientific realists’ speech acts. The atheist’s speech acts go contrary to his belief that God does not exist, and scientific realists’ speech acts go contrary to their belief that our best scientific theories are true. As a result, the atheist’s speech acts mislead his followers into believing that he is Christian. The scientific realists’ speech acts mislead their hearers into believing that they are Kuhnians.

Moore’s Paradox

Such speech acts raise an interesting philosophical issue. Imagine that someone says, “Snow is white, but I don’t believe snow is white.” The assertion of such a sentence involves Moore’s paradox. Moore’s paradox arises when we say a sentence of the form, “P, but I don’t believe p” (Moore, 1993: 207–212). We can push the atheist above to be caught in Moore’s paradox. Imagine that he says, “If you worship God, you’ll go to heaven.” We request him to declare whether he believes or not what he just said. He declares, “I don’t believe if you worship God, you’ll go to heaven.” As a result, he is caught in Moore’s paradox, and he only puzzles his audience.

The same is true of the scientific realists above. Imagine that they say, “Successive paradigms are incommensurable, so present and future scientists would not be able to communicate with each other.” We request them to declare whether they believe or not what they just said. They declare, “I don’t believe successive paradigms are incommensurable, so present and future scientists would not be able to communicate with each other.” As a result, they are caught in Moore’s paradox, and they only puzzle their audience.

Kuhn would also be caught in Moore’s paradox if he draws the analogy between the development of science and the evolution of organisms without committing to the truth of evolutionary theory, pace Bryant. Imagine that Kuhn says, “Organisms don’t evolve towards a goal. Similarly, science doesn’t develop towards truths. I, however, don’t believe organisms don’t evolve towards a goal.” He says, “Organisms don’t evolve towards a goal. Similarly, science doesn’t develop towards truths” in order to draw the analogy between the development of science and the evolution of organisms. He says, “I, however, don’t believe organisms don’t evolve towards a goal,” in order to express his refusal to believe that evolutionary theory is true. It is, however, a Moorean sentence: “Organisms don’t evolve towards a goal. I, however, don’t believe organisms don’t evolve towards a goal.” The assertion of such a sentence gives rise to Moore’s paradox.

Scientific antirealists would also be caught in Moore’s paradox, if they explain phenomena in terms of a scientific theory without committing to the truth of it, pace van Fraassen. Imagine that scientific antirealists say, “The space between two galaxies expands because dark energy exists between them, but I don’t believe that dark energy exists between two galaxies.” They say, “The space between two galaxies expands because dark energy exists between them,” in order to explain why the space between galaxies expands.

They add, “I don’t believe that dark energy exists between two galaxies,” in order to express their refusal to commit to the truth of the theoretical claim that dark energy exists. It is, however, a Moorean sentence: “The space between two galaxies expands because dark energy exists between them, but I don’t believe that dark energy exists between two galaxies.” Asserting such a sentence will only puzzle their audience. Consequently, Moore’s paradox bars scientific antirealists from invoking scientific theories to explain phenomena (Park, 2017b: 383, 2018b: Section 4).

Researchers on Moore’s paradox believe that “contradiction is at the heart of the absurdity of saying a Moorean sentence, but it is not obvious wherein contradiction lies” (Park, 2014: 345). Park (2014: 345) argues that when you say, “Snow is white,” your audience believe that you believe that snow is white. Their belief that you believe that snow is white contradicts the second conjunct of your Moorean sentence that you do not believe that snow is white.

Thus, the contradiction lies in your audience’s belief and the second conjunct of your Moorean sentence. The present paper does not aim to flesh out and defend this view of wherein lies the contradiction. It rather aims to show that Moore’s paradox prevents us from using the language of a scientific theory without committing to the truth of it, pace Bryant and van Fraassen.

The Real Consequences of Speaking What You Don’t Believe

Set Moore’s paradox aside. Let me raise another objection to Bryant and van Fraassen. Imagine that Kuhn encounters a philosopher of mind. The philosopher of mind asserts, “A mental state is reducible to a brain state.” Kuhn realizes that the philosopher of mind espouses the identity theory of mind, but he knows that the identity theory of mind has already been refuted by the multiple realizability argument. So he brings up the multiple realizability argument to the philosopher of mind. The philosopher of mind is persuaded of the multiple realizability argument and admits that the identity theory is not tenable.

To Kuhn’s surprise, however, the philosopher of mind claims that when he said, “A mental state is reducible to a brain state,” he spoke the language of the identity theory without committing to the truth of it, so his position is not refuted by Kuhn. Note that the philosopher of mind escapes the refutation of his position by saying that he did not believe what he stated. It is also reasonable for the philosopher of mind to escape the refutation of his position by saying that he did not believe what he stated, if it is reasonable for Kuhn to escape the refutation of his position by saying that he did not believe what he stated. Kuhn would think that it is not reasonable for the philosopher of mind to do so.

Kuhn, however, might bite the bullet, saying that it is reasonable for the philosopher of mind to do so. The strategy to avoid the refutation, Kuhn might continue, only reveals that the identity theory was not his position after all. Evaluating arguments does not require that we identify the beliefs of the authors of arguments. In philosophy, we only need to care about whether arguments are valid or invalid, sound or unsound, strong or weak, and so on.

Speculating about what beliefs the authors of arguments hold as a way of evaluating arguments is to implicitly rely on an argument from authority, i.e., it is to think as though the authors’ beliefs determine the strength of arguments rather than the form and content of arguments do.

We, however, need to consider under what conditions we accept the conclusion of an argument in general. We accept it, when premises are plausible and when the conclusion follows from the premises. We can tell whether the conclusion follows from the premises or not without the author’s belief that it does. In many cases, however, we cannot tell whether premises are plausible or not without the author’s belief that they are.

Imagine, for example, that a witness states in court that a defendant is guilty because the defendant was in the crime scene. The judge can tell whether the conclusion follows from the premise or not without the witness’s belief that it does. The judge, however, cannot tell whether the premise is plausible or not without the witness’s belief that it is. Imagine that the witness says that the defendant is guilty because the defendant was in the crime scene, but that the witness declares that he does not believe that the defendant was in the crime scene. Since the witness does not believe that the premise is true, the judge has no reason to believe that it is true. It is unreasonable for the judge to evaluate the witness’s argument independently of whether the witness believes or not that the premise is true.

In a nutshell, an argument loses its persuasive force, if the author of the argument does not believe that premises are true. Thus, if you aim to convince your audience that your argument is cogent, you should believe yourself that the premises are true. If you declare that you do not believe that the premises are true, your audience will ask you some disconcerting questions: “If you don’t, why should I believe what you don’t? How can you say to me what you don’t believe? Do you expect me to believe what you don’t?” (Park, 2018b: Section 4).

In case you still think that it is harmless and legitimate to speak what you do not believe, I invite you to imagine that your political rival commits murder to frame you. A false charge is brought to you, and you are tried in court. The prosecutor has a strong indictment against you. You state vehemently that you did not commit murder. You, however, have no physical evidence supporting your statement. Furthermore, you are well-known as a person who speaks vehemently what you do not believe. Not surprisingly, the judge issues a death sentence on you, thinking that you are merely speaking the language of the innocent. The point of this sad story is that speaking what you do not believe may result in a tragedy in certain cases.

A Solution With a Prestigious Inspiration

Let me now turn to a slightly different, but related, issue. Under what condition can I refute your belief when you speak contrary to what you believe? I can do it only when I have direct access to your doxastic states, i.e., only when I can identify your beliefs without the mediation of your language. It is not enough for me to interpret your language correctly and present powerful evidence against what your language conveys.

After all, whenever I present such evidence to you, you will escape the refutation of what you stated simply by saying that you did not believe what you stated. Thus, Bryant’s defense of Kuhn’s position from my criticism above amounts to imposing an excessively high epistemic standard on Kuhn’s opponents. After all, his opponents do not have direct access to his doxastic states.

In this context, it is useful to be reminded of the epistemic imperative: “Act only on an epistemic maxim through which you can at the same time will that it should become a universal one” (Park, 2018c: 3). Consider the maxim “Escape the refutation of your position by saying you didn’t believe what you stated.” If you cannot will this maxim to become a universal one, you ought not to act on it yourself. It is immoral for you to act on the maxim despite the fact that you cannot will it to become a universal maxim. Thus, the epistemic imperative can be invoked to argue that Kuhn ought not to use the language of evolutionary theory without committing to the truth of it, pace Bryant.

Let me now raise a slightly different, although related, issue. Recall that according to Bryant, Kuhn could adopt the language of evolutionary theory without committing to the truth of it. Admittedly, there is an epistemic advantage of not committing to the truth of evolutionary theory on Kuhn’s part. The advantage is that he might avoid the risk of forming a false belief regarding evolutionary theory. Yet, he can stick to his philosophical account of science according to which science does not develop towards truths, and current scientific theories will be supplanted by incommensurable alternatives.

There is, however, an epistemic disadvantage of not committing to the truth of a scientific theory. Imagine that Kuhn is not only a philosopher and historian of science but also a scientist. He has worked hard for several decades to solve a scientific problem that has been plaguing an old scientific theory. Finally, he hits upon a great scientific theory that handles the recalcitrant problem. His scientific colleagues reject the old scientific theory and accept his new scientific theory, i.e., a scientific revolution occurs.

He becomes famous not only among scientists but also among the general public. He is so excited about his new scientific theory that he believes that it is true. Some philosophers, however, come along and dispirit him by saying that they do not believe that his new theory is true, and that they do not even believe that it is closer to the truth than its predecessor was. Kuhn protests that his new theory has theoretical virtues, such as accuracy, simplicity, and fruitfulness. Not impressed by these virtues, however, the philosophers reply that science does not develop towards truths, and that his theory will be displaced by an incommensurable alternative. They were exposed to Kuhn’s philosophical account of science!

Epistemic Reciprocation

They have adopted a philosophical position called epistemic reciprocalism according to which “we ought to treat our epistemic colleagues, as they treat their epistemic agents” (Park, 2017a: 57). Epistemic reciprocalists are scientific antirealists’ true adversaries. Scientific antirealists refuse to believe that their epistemic colleagues’ scientific theories are true for fear that they might form false beliefs.

In return, epistemic reciprocalists refuse to believe that scientific antirealists’ positive theories are true for fear that they might form false beliefs. We, as epistemic agents, are not only interested in avoiding false beliefs but also in propagating “to others our own theories which we are confident about” (Park, 2017a: 58). Scientific antirealists achieve the first epistemic goal at the cost of the second epistemic goal.

Epistemic reciprocalism is built upon the foundation of social epistemology, which claims that we are not asocial epistemic agents but social epistemic agents. Social epistemic agents are those who interact with each other over the matters of what to believe and what not to believe. So they take into account how their interlocutors treat their epistemic colleagues before taking epistemic attitudes towards their interlocutors’ positive theories.

Let me now turn to another of Bryant’s defenses of Kuhn’s position. She says that it is not clear that the analogy between the evolution of organisms and the development of science is integral to Kuhn’s account. Kuhn could “have ascribed the same characteristics to theory change without referring to evolutionary theory at all” (Bryant, 2018: 3). In other words, Kuhn’s contention that science does not develop towards truths rises or falls independently of the analogy between the development of science and the evolution of organisms. Again, this defense of Kuhn’s position is brilliant.

Consider, however, that the development of science is analogous to the evolution of organisms, regardless of whether Kuhn makes use of the analogy to defend his philosophical account of science or not, and that the fact that they are analogous is a strike against Kuhn’s philosophical account of science. Suppose that Kuhn believes that science does not develop towards truths, but that he does not believe that organisms do not evolve towards a goal, despite the fact that the development of science is analogous to the evolution of organisms.

An immediate objection to his position is that it is not clear on what grounds he embraces the philosophical claim about science, but not the scientific claim about organisms, when the two claims parallel each other. It is ad hoc merely to suggest that the scientific claim is untrustworthy, but that the philosophical claim is trustworthy. What is so untrustworthy about the scientific claim, but so trustworthy about the philosophical claim? It would be difficult to answer these questions because the development of science and the evolution of organisms are similar to each other.

A moral is that if philosophers reject our best scientific theories, they cannot make philosophical claims that are similar to what our best scientific theories assert. In general, the more philosophers reject scientific claims, the more impoverished their philosophical positions will be, and the heavier their burdens will be to prove that their philosophical claims are dissimilar to the scientific claims that they reject.

Moreover, it is not clear what Kuhn could say to scientists who take the opposite position in response to him. They believe that organisms do not evolve towards a goal, but refuse to believe that science does not develop towards truths. To go further, they trust scientific claims, but distrust philosophical claims. They protest that it is a manifestation of philosophical arrogance to suppose that philosophical claims are worthy of beliefs, but scientific claims are not.

This possible response to Kuhn reminds us of the Golden Rule: Treat others as you want to be treated. Philosophers ought to treat scientists as they want to be treated, concerning epistemic matters. Suppose that a scientific claim is similar to a philosophical claim. If philosophers do not want scientists to hold a double standard with respect to the scientific and philosophical claims, philosophers should not hold a double standard with respect to them.

There “is no reason for thinking that the Golden Rule ranges over moral matters, but not over epistemic matters” (Park, 2018d: 77–78). Again, we are not asocial epistemic agents but social epistemic agents. As such, we ought to behave in accordance with the epistemic norms governing the behavior of social epistemic agents.

Finally, the present paper is intended to be critical of Kuhn’s philosophy of science while enshrining his insight that science is a social enterprise, and that scientists are social epistemic agents. I appealed to Moore’s paradox, epistemic reciprocalism, the epistemic imperative, and the Golden Rule in order to undermine Bryant’s defenses of Kuhn’s position from my criticism. All these theoretical resources can be used to increase our understanding of science as a social endeavor. Let me add to Kuhn’s insight that philosophers are also social epistemic agents.

Contact details: nature@unist.ac.kr

References

Arnold, Markus. “Is There Anything Wrong with Thomas Kuhn?”, Social Epistemology Review and Reply Collective 7, no. 5 (2018): 42–47.

Byrant, Amanda. “Each Kuhn Mutually Incommensurable”, Social Epistemology Review and Reply Collective 7, no. 6 (2018): 1–7.

Dawes, Gregory. “Belief is Not the Issue: A Defence of Inference to the Best Explanation”, Ratio: An International Journal of Analytic Philosophy 26, no. 1 (2013): 62–78.

Dellsén, Finnur. “Understanding without Justification or Belief”, Ratio: An International Journal of Analytic Philosophy (2016). DOI: 10.1111/rati.12134.

Kuhn, Thomas. The Structure of Scientific Revolutions. 2nd ed. The University of Chicago Press, (1962/1970).

Mizrahi, Moti. “Introduction”, In The Kuhnian Image of Science: Time for a Decisive Transformation? Moti Mizrahi (ed.), London: Rowman & Littlefield, (2018): 1–22.

Moore, George. “Moore’s Paradox”, In G.E. Moore: Selected Writings. Baldwin, Thomas (ed.), London: Routledge, (1993).

Park, Seungbae. “On the Relationship between Speech Acts and Psychological States”, Pragmatics and Cognition 22, no. 3 (2014): 340–351.

Park, Seungbae. “Accepting Our Best Scientific Theories”, Filosofija. Sociologija 26, no. 3 (2015): 218–227.

Park, Seungbae. “Defense of Epistemic Reciprocalism”, Filosofija. Sociologija 28, no. 1 (2017a): 56–64.

Park, Seungbae. “Understanding without Justification and Belief?” Principia: An International Journal of Epistemology 21, no. 3 (2017b): 379–389.

Park, Seungbae. “Can Kuhn’s Taxonomic Incommensurability Be an Image of Science?” In The Kuhnian Image of Science: Time for a Decisive Transformation? Moti Mizrahi (ed.), London: Rowman & Littlefield, (2018a): 61–74.

Park, Seungbae. “Should Scientists Embrace Scientific Realism or Antirealism?”, Philosophical Forum (2018b): (to be assigned).

Park, Seungbae. “In Defense of the Epistemic Imperative”, Axiomathes (2018c). DOI: https://doi.org/10.1007/s10516-018-9371-9.

Park, Seungbae. “The Pessimistic Induction and the Golden Rule”, Problemos 93 (2018d): 70–80.

van Fraassen, Bas. The Scientific Image. Oxford: Oxford University Press, (1980).

Winther, Rasmus. “A Dialogue”, Metascience 18 (2009): 370–379.

Author Information: Amanda Bryant, Trent University, amandabryant@trentu.ca

Bryant, Amanda. “Each Kuhn Mutually Incommensurable.” Social Epistemology Review and Reply Collective 7, no. 6 (2018): 1-7.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-3XM

Image by Denis Defreyne via Flickr / Creative Commons

 

This volume is divided into four parts, in which its contributors variously Question, Defend, Revise, or Abandon the Kuhnian image of science. One immediately wonders: what is this thing, the Kuhnian Image of Science? It isn’t a question that can be decisively or quickly settled, of course. Perhaps one of the reasons why so much has been written on Kuhn’s philosophy of science is that it gives rise to such rich interpretive challenges.

Informed general philosophy of science readers will of course know the tagline version of Kuhn’s view — namely, that the development of science unfolds in wholesale revolutions of scientific paradigms that are in some sense incommensurable with one another. However, one might think that whatever the image of science at issue in this volume is, it should be a sharper image than that.

Many Thomases Kuhn

But of course there isn’t really a single, substantive, cohesive, uncontroversial image at issue. Alexandra Argamakova rightly points out in her contribution, “there exist various images of science belonging to different Thomas Kuhns at different stages of his work life and from different perspectives of interpretation, so the target for current analysis turns out to be less detectable” (46). Rather, the contributors touch on various aspects of Kuhn’s philosophy, variously interpreted — and as such, multiple Kuhnian images emerge as the volume unfolds. That’s just as it should be. In fact, if the volume had propped up some caricature of Kuhn’s views as the Kuhnian image of science, it would have done a disservice both to Kuhn and to his many interpreters.

One wonders, too, whether the so-called Kuhnian image of science is really so broadly endorsed as to be the potential subject of (echoing Kuhn’s own phrase) a ‘decisive transformation’. In his introduction, Moti Mizrahi emphasizes Kuhn’s undeniable influence. Kuhn has, Mizrahi points out, literally tens of thousands of citations; numerous books, articles, and journal issues devoted to his work; and a lasting legacy in the language of academic and public discourse. While all of this signals influence, it’s clearly no indication of agreement.

To be fair, Mizrahi acknowledges the “fair share” of Kuhn critics (2). Nevertheless, if the prospect of decisively transforming the Kuhnian image of science were to be a serious prospect, then the image would have to be widely accepted and enjoy a lasting relevance. However, Argamakova again rightly emphasizes that Kuhn’s philosophy of science “never fully captured the intellectual market” (45) and “could not be less attractive for so many minds!” (47). Moreover, in a remarkable passage in his contribution, Howard Sankey describes a central component of the so-called Kuhnian image of science as as an old battlefield and a dead issue:

Returning to the topic from the perspective of the contemporary scene in the philosophy of science is like visiting a battlefield from a forgotten war. The positions of the warring sides may still be made out. But the battlefield is grown over with grass. One may find evidence of the fighting that once took place, perhaps bullet marks or shell holes. But the fighting ceased long ago. The battle is a thing of the past.

The problem of incommensurability is no longer a live issue. The present chapter has taken the form of a post-mortem examination of a once hotly debated but now largely forgotten problem from an earlier period in the philosophy of science. (87)

If the same holds true for the rest of the Kuhnian image (or images), then the volume isn’t exactly timely.

But dead philosophical issues don’t always stay dead. Or rather, we’re not always right to pronounce them dead. In 1984, Arthur Fine famously proclaimed scientific realism “well and truly dead” (in The Natural Ontological Attitude), and clearly he was quite wrong. At any rate, we may find interest in an issue, dead or not, and there is certainly much of it to be found in this volume. I have been asked to focus my comments on the second half of the book. As such, I will discuss the Introduction, as well as Parts I and II in brief, then I will discuss parts III and IV at greater length.

On the Incommensurable

In his Introduction, Mizrahi argues that, far from initiating a historical turn in the philosophy of science, Kuhn was ‘patient zero’ for anecdotiasis — “the tendency to use cherry-picked anecdotes or case studies… to support general claims (about the nature of science as a whole)” (3). Mizrahi argues that anecdotiasis is pervasive, since significant proportions of articles in the PhilSci-Archive and in leading philosophy of science journals contain the phrase ‘case study’.

But neither using the phrase ‘case study’ nor doing case studies is inherently or self-evidently problematic. Case studies can be interesting, informative, and evidential. Of course the challenges are not to ignore relevant problem cases, not to generalize hastily, and not to assign undue evidential weight to them. But if we are to suppose that all or most philosophers of science who use case studies fail to meet those challenges, we will need a substantial body of evidence.

Part I begins with Mizrahi’s contribution, which the successive contributions all engage. In it, he defines taxonomic incommensurability as conceptual incompatibility between new and old theories. Against those who claim that Kuhn ‘discovered’ incommensurability, Mizrahi argues that there are no good deductive or inductive arguments for taxonomic incommensurability. He cites just two authors, Eric Oberheim and Paul Hoyningen-Huene, who use the language of discovery to characterize incommensurability. As such, it isn’t clear that the assumption Mizrahi takes pains to reject is particularly widespread.

Nevertheless, even if everyone universally agreed that there are no legitimate cases of incommensurability, it would still be useful to know why they’d be justified in so thinking. So the work that Mizrahi does to establish his conclusion is valuable. He shows the dubious sorts of assumptions that arguments for the taxonomic incommensurability thesis would hang on.

Argamakova’s helpful and clear contribution lays out three general types of critique with respect to Kuhn’s view of scientific development — ambiguity, inaccuracy, and limitation — and raises, if tentatively, concerns about Kuhn’s universalist ambitions. She might have been more explicit with respect to the force and scope of her comments on universalism — in particular, whether she sees the flaws in Kuhn’s theory as ultimately stemming from his attempts at universal generalizations, and to what extent her concerns extend beyond Kuhn to general philosophy of science.

Seungbae Park advances several arguments in response to Kuhn’s incommensurability thesis. One such argument takes up Kuhn’s analogy in The Structure of Scientific Revolutions (henceforth Structure) between the development of science and the evolution of organisms. Park suggests that in drawing the analogy, Kuhn illicitly assumes the truth of evolutionary theory. He doesn’t consider that Kuhn could adopt the language of a paradigm (for the purposes of drawing an analogy, no less!) without committing to the literal truth of that paradigm.

Park also claims that “it is self-defeating for Kuhn to invoke a scientific theory to give an account of science that discredits scientific claims” (66), when it’s not clear that the analogy is at all integral to Kuhn’s account. Kuhn could, for instance, have ascribed the same characteristics to theory change without referring to evolutionary theory at all.

Sankey’s illuminating contribution fills in the interpretive background on incommensurability — the semantic version of Kuhn’s incommensurability thesis, in particular. He objects, with Mizrahi, to the language of discovery used by Oberheim and Hoyningen-Huene with respect to incommensurability. He argues, convincingly, that the purported paradigm shift that allowed Kuhn to finally comprehend Aristotle’s physics isn’t a case of incommensurability, but rather of comprehension after an initial failure to understand. While this doesn’t establish his conclusion that no cases of incommensurability have been established (76), it does show that a historically significant purported case is not genuine.

Vasso Kindi fills in some historical detail regarding the positivist image of science that Kuhn sought to replace and the “stereotypical” image attributed to him (96). She argues that Kuhn’s critics (including by implication several of her co-contributors) frequently attack a strawman — that, notwithstanding Kuhn’s avowed deference to history, the Kuhnian image of science is not meant to be a historical representation, and so doesn’t need to be supported by historical evidence. It is, rather, a “a philosophical model that was used to challenge an ideal image of science” (95).

Finally, Lydia Patton emphasizes the practical dimension of Kuhn’s conception of paradigms in Structure. It ought to be uncontroversial that on Kuhn’s early characterization a paradigm is not merely a theory, but a series of epistemic, evaluative, and methodological practices, too. But Patton argues that there has been too strong a semantic tendency in the treatment of Kuhnian paradigms (including by the later Kuhn himself). She argues for the greater interest and value of a practical lens on Kuhn’s project for the purposes of understanding and explaining science.

Vectors of Glory

Andrew Aberdein’s contribution deals with the longstanding and intriguing question of whether there are revolutions in mathematics. He imports to that discussion distinctions he drew in previous work among so-called glorious, inglorious, and paraglorious revolutions, in which, respectively, key components of the theory are preserved, lost, or preserved with new additions. Key components are, he says, “at least all components without which the theory could not be articulated” (136).

He discusses several examples of key shifts in mathematical theory and practice that putatively exemplify certain of these classes of revolution. The strength of the paper is its fascinating examples, particularly the example of Inter-Universal Teichmüller theory, which, Aberdein explains, introduces such novel techniques and concepts that some leading mathematicians say its proofs read as if they were “from the future, or from outer space” (145).

Aberdein doesn’t falsely advertise his thesis. He acknowledges that “it is not easy to determine whether a given episode is revolutionary” (140), and claims only that certain shifts “may be understood” as revolutionary (149) — that the cases he offers are putative mathematical revolutions. As to how we should go about identifying putative mathematical revolutions, Aberdein suggests we look directly for conceptual shifts (or ‘sorites-like’ sequences of shifts) in which key components have been lost or gained.

A fuller discussion of these diagnostics is needed, since the judgment of whether there are revolutions (genuine or putative) in mathematics will hang largely on diagnostics such as these. Is any key conceptual shift sufficient? If so, have we really captured the spirit of Kuhn’s view, given that Kuhn seems to ascribe a certain momentousness to revolutions? If the conceptual shift has to be substantial, how substantial, and how should we gauge its substantiality? Without some principled, non-arbitrary, and non-question-begging standards for what counts as a revolution, we cannot hope to give a serious answer to the question of whether there are, even putatively, revolutions in mathematics.

The paper would also have benefited from a more explicit discussion of what a mathematical paradigm is in the first place, especially as compared to a scientific one. We can infer from Aberdein’s examples that conceptions of number, ratio, proportion, as well as systems of conjecture and mathematical techniques belong to mathematical paradigms — but explicit comment on this would have been beneficial.

Moreover, Aberdein sees an affinity between mathematics and science, commenting toward the end of the paper that the methodology of mathematics is not so different from that of science, and that “the story we tell about revolutions [should] hold for both science and mathematics” (149). These are loaded comments needing further elaboration.

The Evolution of Thomas Kuhn

In his contribution, James Marcum argues that Kuhn’s later evolutionary view is more relevant to current philosophy of science (being ‘pluralistic and perspectival’) than his earlier revolutionary one. On Kuhn’s later evolutionary view, Marcum explains, scientific change proceeds via “smaller evolutionary specialization or speciation” (155), with a “gradual emergence of a specialty’s practice and knowledge” (159). On this view, scientific development consists in “small incremental changes of belief” rather than “the upheaval of world-shattering revolutions” (159).

Marcum uses the emergence of bacteriology, virology, and retrovirology to illustrate the strengths and weaknesses of Kuhn’s evolutionary view. Its main strength, he says, is that it illuminates the development of and relationships among these sorts of scientific specialties; its weakness is that it ascribes a single tempo — Darwinian gradualism — and a single mode — speciation — to the evolution of science. Marcum adopts George Gaylord Simpson’s “richer and more textured approach” (165), which distinguishes several tempos and modes. Since these refinements better enable Kuhn’s view to handle a range of cases, they are certainly valuable.

According to Marcum, current philosophy of science is ‘pluralistic and perspectival’ in its recognition that different sciences face different philosophical issues and in its inclusion of perspectives from outside the logico-analytic tradition, such as continental, pragmatist, and feminist perspectives (166). Marcum seems right to characterize current philosophy of science as pluralistic, given the move away from general philosophy of science to more specialized branches.

If this pluralism is to be embraced, one might wonder what role (if any) remains for general philosophy of science. Marcum makes the interesting suggestion that a general image of science, like Kuhn’s evolutionary image, while respecting our contemporary pluralistic stance, can at the same time offer “a type of unity among the sciences, not in terms of reducing them to one science, but rather with respect to mapping the conceptual relationships among them” (169).

One of Marcum’s central aims is to show that incommensurability plays a key explanatory role in a refined version of Kuhn’s evolutionary image of science. The role of incommensurability on this view is to account for scientific speciation. However, Marcum shows only that we can characterize scientific speciation in terms of incommensurability, without clearly establishing the explanatory payoff of so doing. He does not succeed in showing that incommensurability has a particularly enriching explanatory role, much less that incommensurability is “critical for conceptual evolution within the sciences” or “an essential component of… the growth of science” (168).

All a Metaphor?

Barbara Gabriella Renzi and Giulio Napolitano frame their contribution with a discussion of competing accounts of the nature and role of metaphor. They avow the commonly accepted view that metaphors are not merely linguistic, but cognitive, and that they are ubiquitous. They claim, I would think uncontroversially, that metaphors shape how individuals approach and reason about complex issues. They also discuss historical empiricist attitudes toward metaphor, competing views on the role of models and metaphor in science, and later, the potential role of metaphor in social domination.

Renzi and Napolitano also address Kuhn’s use of the metaphor of Darwinian evolution to characterize scientific change. They suggest that an apter metaphor for scientific change can be made of the obsolete orthogenetic hypothesis, according to which “variations are not random but directed by forces regulated and ultimately directed by the internal constitution of the organism, which responds to environmental stimuli” (184).

The orthogenetic metaphor is a better fit for scientific change, they argue, because the emergence of new ideas in science is not random, but driven by “arguments and debates… specific needs of a scientist or group of scientists who have been seeking a solution to a problem” (184).

The orthogenetic metaphor effectively highlights a drawback of the Darwinian metaphor that might otherwise be overlooked, and deserves further attention. The space devoted to discussing metaphor in the abstract contributes little to the paper, beyond prescriptions to take metaphor seriously and approach it with caution. Much of that space would have been better devoted to using historical examples to compare Kuhn’s Darwinian metaphor to the proposed orthogenetic alternative, to make concrete the fruitfulness of the latter, and to flesh out the specific kinds of internal and external pressures that Renzi and Napolitano see as important drivers of scientific change.

Methodological Contextualism

Darrell Rowbottom offers a summary and several criticisms of what he sees as Kuhn’s early-middle period image of science. By way of criticism, he points out that it isn’t clear how to individuate disciplinary matrices in a way that preserves a clear distinction between normal and extraordinary science, or ensures that what Kuhn calls ‘normal science’ is really the norm. Moreover, in linking the descriptive and normative components of his view, Kuhn implausibly assumes that mature science is optimal.

Rowbottom suggests a replacement image of science he calls methodological contextualism (developed more fully in previous work). Methodological contextualism identifies several roles — puzzle-solving, critical, and imaginative — which scientific practitioners fulfill to varying degrees and in varying combinations. The ideal balance of these roles depends on contextual factors, including the scientists available and the state of science (200).

The novel question Rowbottom considers in this paper is: how could piecemeal change in science be rational from the perspective of methodological contextualism? I have difficulty seeing why this is even a prima facie problem for Rowbottom’s view, since puzzle-solving, critical and imaginative activities are clearly consonant with piecemeal change. I suppose it is because the view retains some of Kuhn’s machinery, including his notion of a disciplinary matrix.

At any rate, Rowbottom suggests that scientists may work within a partial disciplinary matrix, or a set of partially overlapping ones. He also makes the intriguing claim that “scientists might allow inconsistency at the global level, and even welcome it as a better alternative than a consistent system with less puzzle-solving power” (202). One might object that Kuhn’s incommensurability thesis seems to block the overlapping matrix move, but Rowbottom proclaims that the falsity of Kuhn’s incommensurability thesis follows “as a consequence of the way that piecemeal change can occur” (201). One person’s modus ponens is another’s modus tollens, as they say.

A Digestible Kuhn

The brevity of the contributions makes them eminently digestible and good potential additions to course syllabi at a range of levels; on the other hand, it means that some of the most provocative and topical themes of the book — such as the epistemic and methodological status of generalizations about science and the role of general philosophy of science in contemporary philosophy — don’t get the full development they deserve. The volume raises more questions than it satisfactorily addresses, but several of them bring renewed relevance and freshness to Kuhnian philosophy of science and ought to direct its future course.

Contact details: amandabryant@trentu.ca

References

Mizrahi, Moti (Ed.) The Kuhnian Image of Science: Time for a Decisive Transformation? Lanham, MD: Rowman & Littlefield, 2018.

Author Information: Markus Arnold, University of Klagenfurt, markus.arnold@aau.at

Arnold, Markus. “Is There Anything Wrong with Thomas Kuhn?.” Social Epistemology Review and Reply Collective 7, no. 5 (2018): 42-47.

The pdf of the article gives specific page references: Shortlink: https://wp.me/p1Bfg0-3Xs

Image by Rob Thomas via Flickr / Creative Commons

 

Twenty-two years after his death, Thomas Kuhn’s work is still able to provoke lively debates, where arguments are exchanged and competing interpretations of his theories are advanced. The Kuhnian Image of Science is a good example, as the book brings together ten scholars in a debate for and against Thomas Kuhn’s legacy. The question, the edited volume raises, is straightforward:

“Does the Kuhnian image of science provide an adequate model of scientific change? If we abandon the Kuhnian picture of revolutionary change and incommensurability […], what consequences would follow from that vis-à-vis our understanding of science as a social, epistemic endeavor?” (7)

In this review I will concentrate on the first two parts of the book, i.e. and in particular on the debate between those who are questioning (Mizrahi, Argamakova, Park, Sankey), and those who are defending Kuhn (Kindi, Patton), since their arguments are closely related. Therefore, I will discuss some of their major arguments in topological order.

Debating Kuhn’s Evidence

The editor Moti Mizrahi opens the debate in his introduction with a confrontational thesis: Kuhn, in his opinion, is responsible for an “infectious disease” (3), for “the pathological state of the field of philosophy of science in general, and general philosophy of science in particular” (3). Kuhn’s vice is his use of case studies (from the history of science) as arguments, although – according to Moti Mizrahi – they are nothing more than “anecdotal evidence” leading to “hasty generalizations” and “fallacious inductive reasoning” (6).

Hearing the trumpets of the troops ready to battle one is eager to learn how to do it right: How the standards of inductive reasoning within philosophy of science are re-erected. Yet, anticipating one of the results of this review, the “inductive reasoning” intended to refute Kuhn’s incommensurability thesis (found in the first part of the book) is actually its weakest part.

However, to understand the intricacy of this difficult task, we have to recognize, that it is not easy to support or falsify inductively a complex theory of science. Broadly speaking, in Kuhn’s account we should empirically observe sciences displaying at least four different manifestations: (1.) “proto-science” in the pre-paradigm phase, when there is no general consensus about theories, methods and standards, (2.) “normal science”, when scientists are most of the time focused on preserving, but also adapting existing paradigms to new problems and new scientific fields, (3.) sciences in a state of crisis, when more and more “anomalies” occur, which defy explanations in conformity with established procedures, and finally (4.) on rare occasions a “revolutionary” state, when different paradigms compete with each other and scientific theories based on one paradigm are to some extent “incommensurable” with those based on another paradigm.

There are good reasons to suppose that Kuhn’s somehow schematic and ideal-typical description of scientific change is too simple compared with the complexities shown by many historical case studies. Nevertheless, the counter-arguments under consideration brought forward against his model seem, paradoxically, to underestimate the complexity of Kuhn’s claims. For example, in Kuhn’s Incommensurability Thesis Mizrahi decides to discuss scientific change only in general.  He claims that Kuhn argues:

“Scientific change (specifically, revolutionary change) is characterized by taxonomic incommensurability.” (33)

The compounded phrase “[s]cientific change (specifically, revolutionary change)” indicates that, in Mizrahi’s interpretation, for Kuhn not all scientific change is per definition revolutionary. But then arguments against Kuhn’s theory should consider at least two kinds of scientific change separately: revolutionary change and those (commensurable) non-revolutionary scientific changes within “normal science.”

Keeping in mind that for Kuhn theory change is possible to a certain degree within normal science (only changing paradigms must be averted)[1], it is not clear, why Kuhn’s “image of science” should be dismissed because “as far as theory change is concerned” taxonomic incommensurability “is the exception rather than the rule” (38).[2]

Or another example, in Can Kuhn’s Taxonomic Incommensurability Be an Image of Science? where Seungbae Park comes to the conclusion that historical evidence shows that “scientific revolution is rare, taxonomic incommensurability is rare, and taxonomic commensurability is common” (61). It is, for similar reasons, unclear why this conclusion should not be commensurable with Kuhn’s description of normal science, since Kuhn claimed that normal science is common and scientific revolutions are rare.

However, this is not Park’s last argument about scientific change: He asks furthermore if we should not distinguish between the distant scientific past, when scientific revolutions were more common, and the recent past, “since most recent past theories have been stable, most present theories will also be stable” (70). Kuhn’s theory of revolutionary paradigm change is, in his opinion, first of all not appropriate for understanding the development of contemporary and future science.

Incommensurable Paradigms of Language?

After a discussion of the critical reception of Thomas Kuhn’s and Paul Feyerabend’s work and the objections raised against their claim that scientific theories or paradigms are incommensurable, Howard Sankey admits in The Demise of the Incommensurability Thesis that:

“the idea that there is conceptual change in science now seems commonplace. But the much-feared consequences, such as incomparability, communication breakdown, and irrationality now all seem to have been greatly overblown.” (88)

Prima facie it seems like a self-critical admission of an inappropriate former reception of Kuhn’s theory of incommensurability, especially by those philosophers of science who tried to fight “irrationality” with the means of referential semantics. However, Sankey seems to think that the dissolution of the exaggerated accusations of Kuhn’s critics somehow makes now Kuhn’s theory of incommensurability obsolete. Hence, Sankey can summarize:

“with the demise of the incommensurability thesis, the debate about scientific realism is free to proceed in a manner that is unencumbered by the semantic concerns about wholesale referential discontinuity that were prompted by the incommensurability thesis.” (88)

For Sankey, Kuhn’s concept of incommensurability is dead (87). He seems to blame Kuhn for the misguided interpretations of his opponents. It comes down to the argument: if it’s not possible to criticize Kuhn’s concept of incommensurability as “irrational” anymore, then Kuhn’s concept cannot claim any relevance for future discussions.

However, more importantly: These arguments against Kuhn are based on referential semantics, i.e. semantic concerns about referential continuity. Hence, what their objections against Kuhn’s incommensurability theory inadvertently show is, paradoxically, the incommensurability of competing paradigms of language. This becomes apparent, for example, when Mizrahi criticizes Kuhn’s sometimes-vague formulations, especially in his early Structure. Mizrahi refers to statements where Kuhn argues with caution:

“The normal-scientific tradition that emerges from a scientific revolution is not only incompatible but often [sic] actually incommensurable with that which has gone before.” (Kuhn 1996, 103)

Formulations such as this prompt Mizrahi to ask: If taxonomic incommensurability (TI):

“is not a general thesis about the nature of scientific change, then what is its explanatory value? How does (TI) help us in terms of understanding the nature of scientific change? On most accounts of explanation, an explanans must have some degree of generality […] But if (TI) has no degree of generality, then it is difficult to see what the explanatory value of (TI) is.” (37)

Kuhn could have responded that his arguments in Structure are explicitly based on Wittgenstein’s theory of “language games” with its central concept of “family resemblance”, which by definition does not allow the assumption that there are unambiguous conceptual boundaries and a distinguishing characteristic, which all or even most of the phenomena aligned by a concept have in common.[3]

Indeed, understanding Wittgenstein’s concept of “family resemblance” is central to understand Kuhn’s theory of “paradigms”, “paradigm shifts”, and the meaning of “incommensurability”.[4] Yet, it is possible to come to similar conclusions without referring to the late Wittgenstein: For example, Alexandra Argamakova despite of her negative evaluation of many of Kuhn’s arguments, unlike Mizrahi, is closer on this issue to Kuhn where she claims in Modeling Scientific Development: “distinct breakthroughs in science can be marked as revolutions, but no universal system of criteria for such appraisal can be formulated in a normative philosophical manner” (54).

Defending Kuhn’s Epistemology

In two of the book’s most interesting discussions of Kuhn’s epistemology, Vasso Kandi’s The Kuhnian Straw Man and Lydia Patton’s Kuhn, Pedagogy, and Practice, the allegation that Kuhn developed his theory on the basis of selected historical cases is refuted. Furthermore, Kindi, defending the innovative character of Kuhn’s work asks “for a more faithful reading”:

“Kuhn’s new image of science, which is actually a mosaic of different traditions, was not put together by generalizing from instances; it emerged once attention was drawn to what makes scientific practice possible, namely paradigms and what follows from them (normal science, anomalies, revolutions). In accordance with Kuhn’s own understanding of scientific revolutions, his revolution in the perception of science did not have to summon new facts or make new discoveries; it only needed a new perspective.” (104)

While Lydia Patton forcefully argues that:

“Kuhn’s original work did not restrict ‘paradigm’ to ‘theoretical framework’, nor did he restrict the perspective of scientific practice to the content of propositions with a truth-value. And it is mainly because Kuhn’s arguments in Structure are outside the semantic view, and focus instead on the practice of science, that they are interesting and fresh.” (124)

Both, Patton and Kindi, offer a close reading of Kuhn’s work, trying to give new perspectives on some of the more contested concepts in Kuhn’s epistemology.

The Social in Social Epistemology

One explicit aim of this edited volume is, as the editor asserts, to outline what consequences would follow from this debate for “our understanding of science as a social, epistemic endeavor” (7). But for this reviewer it is not obvious how the strong emphasis on discounting Kuhn’s incommensurability thesis in the first part of the book should lead to a better understanding of science as a social practice.

Kuhn’s theory of incommensurability of competing paradigms is precisely the point within his epistemology where value judgments and social decisions come into play. While traditionally those who defended the “progress of science” (cf. Sankey: 87) against what they saw as Kuhn’s “anti-realist” position were often those who wanted to defend the objectivity of science by excluding “external” influences, like the “social” and the political, from the scientific core.[5]

It is therefore important when talking about incommensurability of paradigms, and the possibility of a “communication breakdown”, to distinguish between two distinct meanings: (a) the impossibility to communicate at all because people do not understand each other’s language or paradigms and (b) the decision after a long and futile debate to end any further communication as a waste of time since no agreement can be reached. It is this second meaning, describing a social phenomenon, which is very common in science. Sankey argues against the first meaning when he declares:

“Given that scientists are able to understand what is said by theories whose terms are untranslatable into their own, no insuperable obstacle stands in the way of full communication between the ‘proponents of competing paradigms.’” (87)

While Sankey “wonders what all the fuss was about” (87), he has only shown (in accordance with Kuhn: cf. Kuhn 2000) that in theory full communication may be possible, but not that communication breakdowns are not common between scientists working with different paradigms. While on a theoretical level these workday problems to communicate may seem, for some philosophers of science, trivial. However, on the social level for working scientists, such communication breakdowns are often not only the reason for fraught relations between colleagues, but also for disciplinary segmentation and sometimes for re-drawing boundaries of scientific disciplines.

Perhaps it is no coincidence that in this volume those who discuss social as well as epistemological practices of scientists are not those who criticize incommensurability from a semantic point of view. Social and epistemological practices are considered in one way or the other by those defending Kuhn, like Kindi and Patton, and those whose main concern is to revise certain aspects of Kuhn’s image of science, like James A. Marcum, Barbara Gabriella Renzi & Giulio Napolitano, and David P. Rowbottom.

However, as I confined this review to the discussion of the first six articles I can only point out that the four remaining articles go beyond the topics discussed thus far and would deserve not only attentive readers but also a thorough discussion. They analyze, for example, scientific revolutions in mathematics (Andrew Aberdein), the role of evolutionary metaphors (Gabriella Renzi/Napolitano, Marcum) and of methodological contextualism in the philosophy of science (Rowbottom). Hence, although this edited volume has some weaknesses, there are several contributions, which open new avenues of thought about Kuhn, and are worth reading for those interested in Kuhn and in philosophy of science.

Contact details: markus.arnold@aau.at

References

Kuhn, Thomas S. The Structure of Scientific Revolutions. Chicago: University of Chicago Press, 1996.

Kuhn, Thomas S. „Commensurability, Comparability, Communicability,“ In Thomas S. Kuhn, Thomas S. The Road Since Structure. Philosophical Essays, 1970-1993, 33-57. Chicago: University of Chicago Press, 2000.

Mizrahi, Moti (Ed.) The Kuhnian Image of Science. Time for a Decisive Transformation? Lanham, MD: Rowman & Littlefield, 2018.

Wittgenstein, Ludwig. Philosophische Untersuchungen / Philosophical Investigations. Transl. by G. E. M. Anscombe, P. M. S. Hacker and Joachim Schulte. Oxford: Wiley-Blackwell, 2009.

[1] Kuhn discusses this type of theory change, for example, as divergent „articulation(s) of the paradigm“ (Kuhn 1996, 83; cf. Kuhn 1996, 23, 29-34, 122).

[2] Always on condition that, like Moti Mizrahi in this argument, we accept the concept of „incommensurability“ as defined by referential semantics. On some problems with „referential continuity“ as main argument against incommensurability see further below.

[3] “Instead of pointing out something common to all […], I’m saying that these phenomena have no one thing in common in virtue of which we use the same word for all – but there are many different kinds of affinity between them“ (Wittgenstein 2009, § 65) “I can think of no better expression to characterize these similarities than “family resemblances”; for the various resemblances between members of a family – build, features, colour of eyes, gait, temperament, and so on and so forth – overlap and criss-cross in the same way.” (§ 67)

[4] Cf. Kuhn 1996, Ch. 5. Later, Kuhn argued explicitly against referential semantics but then on the basis of a hermeneutic (holistic) theory of language (Kuhn 2000; but cf. Kuhn 1996, 128f.).

[5] This, despite the fact that Kuhn himself tried to restrict the relevant „social“ factors in his epistemology to social dynamics within scientific communities.

Author Information: Stephen Turner, University of South Florida, turner@usf.edu

Turner, Stephen. “Fuller’s roter Faden.” Social Epistemology Review and Reply Collective 7, no. 5 (2018): 25-29.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-3WX

Art by William Blake, depicting the creation of reality.
Image via AJC1 via Flickr / Creative Commons

The Germans have a notion of “research intention,” by which they mean the underlying aim of an author’s work as revealed over its whole trajectory. Francis Remedios and Val Dusek have provided, if not an account itself, the material for an account of Steve Fuller’s research intention, or as they put it the “thread” that runs through his work.

These “intentions” are not something that is apparent to the authors themselves, which is part of the point: at the start of their intellectual journey they are working out a path which leads they know not where, but which can be seen as a path with an identifiable beginning and end retrospectively. We are now at a point where we can say something about this path in the case of Fuller. We can also see the ways in which various Leitmotifs, corollaries, and persistent themes fit with the basic research intention, and see why Fuller pursued different topics at different times.

A Continuity of Many Changes

The ur-source for Fuller’s thought is his first book, Social Epistemology. On the surface, this book seems alien to the later work, so much so that one can think of Fuller as having a turn. But seen in terms of an underlying research intention, and indeed in Fuller’s own self-explications included in this text, this is not the case: the later work is a natural development, almost an entailment, of the earlier work, properly understood.

The core of the earlier work was the idea of constructing a genuine epistemology, in the sense of a kind of normative account of scientific knowledge, out of “social” considerations and especially social constructivism, which at the time was considered to be either descriptive or anti-epistemological, or both. For Fuller, this goal meant that the normative content would at least include, or be dominated by, the “social” part of epistemology, considerations of the norms of a community, norms which could be changed, which is to say made into a matter of “policy.”

This leap to community policies leads directly to a set of considerations that are corollaries to Fuller’s long-term project. We need an account of what the “policy” options are, and a way to choose between them. Fuller was trained at a time when there was a lingering controversy over this topic: the conflict between Kuhn and the Popperians. Kuhn represented a kind of consensus driven authoritarianism. For him it was right and necessary for science to be organized around ungroundable premises that enabled science to be turned into puzzle-solving, rather than insoluble disputes over fundamentals. These occurred, and produced new ungroundable consensual premises, at the rare moments of scientific revolutions.

Progress was possible through these revolutions, but our normal notions of progress were suspended during the revolutions and applied only to the normal puzzle-solving phase of science. Popperianism, on the contrary, ascribed progress to a process of conjecture and refutation in which ever broader theories developed to account for the failures of previous conjectures, in an unending process.

Kuhnianism, in the lens of Fuller’s project in Social Epistemology, was itself a kind of normative epistemology, which said “don’t dispute fundamentals until the sad day comes when one must.” Fuller’s instincts were always with Popper on this point: authoritarian consensus has no place in science for either of them. But Fuller provided a tertium quid, which had the effect of upending the whole conflict. He took over the idea of the social construction of reality and gave it a normative and collective or policy interpretation. We make knowledge. There is no knowledge that we do not create.

The creation is a “social” activity, as the social constructivists claimed. But this social itself needed to be governed by a sense of responsibility for these acts of creation, and because they were social, this meant by a “policy.” What this policy should be was not clear: no one had connected the notion of construction to the notion of responsibility in this way. But it was a clear implication of the idea of knowledge as a product of making. Making implies a responsibility for the consequences of making.

Dangers of Acknowledging Our Making

This was a step that few people were willing to take. Traditional epistemology was passive. Theory choice was choice between the theories that were presented to the passive chooser. The choices could be made on purely epistemic grounds. There was no consideration of responsibility, because the choices were an end point, a matter of scientific aesthetics, with no further consequences. Fuller, as Remedios and Dusek point out, rejects this passivity, a rejection that grows directly out of his appropriation of constructivism.

From a “making” or active epistemic perspective, Kuhnianism is an abdication of responsibility, and a policy of passivity. But Fuller also sees that overcoming the passivity Kuhn describes as the normal state of science, requires an alternative policy, which enables the knowledge that is in fact “made” but which is presented as given, to be challenged. This is a condition of acknowledging responsibility for what is made.

There is, however, an oddity in talking about responsibility in relation to collective knowledge producing, which arises because we don’t know in advance where the project of knowledge production will lead. I think of this on analogy to the debate between Malthus and Marx. If one accepts the static assumptions of Malthus, his predictions are valid: Marx made the productivist argument that with every newborn mouth came two hands. He would have been better to argue that with every mouth came a knowledge making brain, because improvements in food production technology enabled the support of much larger populations, more technology, and so forth—something Malthus did not consider and indeed could not have. That knowledge was in the future.

Fuller’s alternative grasps this point: utilitarian considerations from present static assumptions can’t provide a basis for thinking about responsibility or policy. We need to let knowledge production proceed regardless of what we think are the consequences, which is necessarily thinking based on static assumptions about knowledge itself. Put differently, we need to value knowledge in itself, because our future is itself made through the making of knowledge.

“Making” or “constructing” is more than a cute metaphor. Fuller shows that there is a tradition in science itself of thinking about design, both in the sense of making new things as a form of discovery, and in the sense of reverse engineering that which exists in order to see how it works. This leads him to the controversial waters of intelligent design, in which the world itself is understood as, at least potentially, the product of design. It also takes us to some metaphysics about humans, human agency, and the social character of human agency.

One can separate some of these considerations from Fuller’s larger project, but they are natural concomitants, and they resolve some basic issues with the original project. The project of constructivism requires a philosophical anthropology. Fuller provides this with an account of the special character of human agency: as knowledge maker humans are God-like or participating in the mind of God. If there is a God, a super-agent, it will also be a maker and knowledge maker, not in the passive but in the active sense. In participating in the mind of God, we participate in this making.

“Shall We Not Ourselves Have to Become Gods?”

This picture has further implications: if we are already God-like in this respect, we can remake ourselves in God-like ways. To renounce these powers is as much of a choice as using them. But it is difficult for the renouncers to draw a line on what to renounce. Just transhumanism? Or race-related research? Or what else? Fuller rejects renunciation of the pursuit of knowledge and the pursuit of making the world. The issue is the same as the issue between Marx and Malthus. The renouncers base their renunciation on static models. They estimate risks on the basis of what is and what is known now. But these are both things that we can change. This is why Fuller proposes a “pro-actionary” rather than a precautionary stance and supports underwriting risk-taking in the pursuit of scientific advance.

There is, however, a problem with the “social” and policy aspect of scientific advance. On the one hand, science benefits humankind. On the other, it is an elite, even a form of Gnosticism. Fuller’s democratic impulse resists this. But his desire for the full use of human power implies a special role for scientists in remaking humanity and making the decisions that go into this project. This takes us right back to the original impulse for social epistemology: the creation of policy for the creation of knowledge.

This project is inevitably confronted with the Malthus problem: we have to make decisions about the future now, on the basis of static assumptions we have no real alternative to. At best we can hint at future possibilities which will be revealed by future science, and hope that they will work out. As Remedios and Dusek note, Fuller is consistently on the side of expanding human knowledge and power, for risk-taking, and is optimistic about the world that would be created through these powers. He is also highly sensitive to the problem of static assumptions: our utilities will not be the utilities of the creatures of the future we create through science.

What Fuller has done is to create a full-fledged alternative to the conventional wisdom about the science society relation and the present way of handling risk. The standard view is represented by Philip Kitcher: it wishes to guide knowledge in ways that reflect the values we should have, which includes the suppression of certain kinds of knowledge by scientists acting paternalistically on behalf of society.

This is a rigidly Malthusian way of thinking: the values (in this case a particular kind of egalitarianism that doesn’t include epistemic equality with scientists) are fixed, the scientists ideas of the negative consequences of something like research on “racial” differences are taken to be valid, and policy should be made in accordance with the same suppression of knowledge. Risk aversion, especially in response to certain values, becomes the guiding “policy” of science.

Fuller’s alternative preserves some basic intuitions: that science advances by risk taking, and by sometimes failing, in the manner of Popper’s conjectures and refutations. This requires the management of science, but management that ensures openness in science, supports innovation, and now and then supports concerted efforts to challenge consensuses. It also requires us to bracket our static assumptions about values, limits, risks, and so forth, not so much to ignore these things but to relativize them to the present, so that we can leave open the future. The conventional view trades heavily on the problem of values, and the potential conflicts between epistemic values and other kinds of values. Fuller sees this as a problem of thinking in terms of the present: in the long run these conflicts vanish.

This end point explains some of the apparent oddities of Fuller’s enthusiasms and dislikes. He prefers the Logical Positivists to the model-oriented philosophy of science of the present: laws are genuinely universal; models are built by assuming present knowledge and share the problems with Malthus. He is skeptical about science done to support policy, for the same reason. And he is skeptical about ecologism as well, which is deeply committed to acting on static assumptions.

The Rewards of the Test

Fuller’s work stands the test of reflexivity: he is as committed to challenging consensuses and taking risks as he exhorts others to be. And for the most part, it works: it is an old Popperian point that only through comparison with strong alternatives that a theory can be tested; otherwise it will simply pile up inductive support, blind to what it is failing to account for. But as Fuller would note, there is another issue of reflexivity here, and it comes at the level of the organization of knowledge. To have conjectures and refutations one must have partners who respond. In the consensus driven world of professional philosophy today, this does not happen. And that is a tragedy. It also makes Fuller’s point: that the community of inquirers needs to be managed.

It is also a tragedy that there are not more Fullers. Constructing a comprehensive response to major issues and carrying it through many topics and many related issues, as people like John Dewey once did, is an arduous task, but a rewarding one. It is a mark of how much the “professionalization” of philosophy has done to alter the way philosophers think and write. This is a topic that is too large for a book review, but it is one that deserves serious reflection. Fuller raises the question by looking at science as a public good and asking how a university should be organized to maximize its value. Perhaps this makes sense for science, given that science is a money loser for universities, but at the same time its main claim on the public purse. For philosophy, we need to ask different questions. Perhaps the much talked about crisis of the humanities will bring about such a conversation. If it does, it is thinking like Fuller’s that will spark the discussion.

Contact details: turner@usf.edu

References

Remedios, Francis X., and Val Dusek. Knowing Humanity in the Social World. The Path of Steve Fuller’s Social Epistemology. New York: Palgrave MacMillan, 2018.