Archives For scientific controversy

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

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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: 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 Kevin Krejci via Flickr / Creative Commons

 

“If you cry ‘Forward!’ you must without fail make plain in what direction to go. Don’t you see that if, without doing so, you call out the word to both a monk and a revolutionary they will go in directions precisely opposite?” – Anton Chekhov

“I’m better with code than with words though.” – Satoshi Nakamoto[1]

Did Satoshi Nakamoto, the pseudonymous creator of Bitcoin, actually invent anything new that had not previously existed before? Should people stop referring to a ‘blockchain revolution’ and instead call blockchain a ‘technological evolution’ that happened gradually and was caused randomly by environmental pressures rather than the intentional acts of a unique inventor? These basic questions make up the core of this paper, along with the suggestion that an alternative way of describing blockchain development makes considerably more sense than using the concept of ‘evolution’ in the digital era.

While it is unoriginal to ask whether blockchain distributed ledger technology should be thought of as an ‘evolution’ or a ‘revolution,’ since many people have asked it already (see bibliography below, including texts and videos), in this paper I’ll go a step deeper by looking at what people actually mean when they refer to blockchain as either an ‘evolution’ or a ‘revolution,’ or rather inconsistently as both at the same time.

In short, I’ll distinguish between their colloquial, ideological and technical uses and ask if one, both or neither of these terms is accurate of the changes blockchain has made, is making and will make as a new global digital technology.

Introduction: From the Book of Satoshi

In the Foreword to The Book of Satoshi: The Collected Writings of Bitcoin Creator Satoshi Nakamoto, libertarian Bitcoin activist Jeff Berwick wrote: “Bitcoin has changed everything. Its importance as an evolution in money and banking cannot be overstated. Notice I don’t use the word ‘revolution’ here because I consider Bitcoin to be a complete ‘evolution’ from the anachronistic money and banking systems that humanity has been using—and been forced by government dictate to use—for at least the last hundred years.” (2014: xvii)

While I don’t really understand what he means by a ‘complete evolution,’ Berwick’s attention to the difference in meaning between ‘evolution’ and ‘revolution’ regarding Bitcoin nevertheless sets the stage for this exploration of blockchain technology, as we consider its current development trajectory. Which term is more suitable?

Worth noting, nowhere in Satoshi Nakamoto’s collected writings is either the term ‘evolution’ or ‘revolution’ to be found. Berwick’s interpretation of ‘blockchain evolution,’ framed within his worldview as an anarcho-capitalist, is thus of his own making and not one that derives from Nakamoto himself. I’ll touch on why I believe that is below. Also of note, the book’s writer and compiler of Nakamoto’s writings, Phil Champagne, states that, “Bitcoin, both a virtual currency and a payment system, represents a revolutionary concept whose significance quickly becomes apparent with a first transaction. … Bitcoin has therefore clearly sparked a new technological revolution that capitalizes on the Internet, another innovation that changed the world.” (2014: 2, 7)

Champagne closes the book stating, “Satoshi Nakamoto brought together many existing mathematical and software concepts to create Bitcoin. Since then, Bitcoin has been an ongoing experiment, continuing to evolve and be updated on a regular basis. It has, so far, proven its utility and revolutionized the financial and monetary industry, particularly the electronic payment system, and is being accepted worldwide.” (2014: 347) The use of both ‘evolution’ and ‘revolution’ in past and present tense shows a debate exists even within this one book about which term best fits blockchain’s current and future status in society.

This paper will look closely at the difference between these two terms as they relate to blockchain, largely staying away from speculation about cryptocurrencies, i.e. digital tokens, crypto-assets, and/or crypto-securities. It will primarily serve to catalogue the way people have used these two terms with respect to blockchain and cryptocurrency and ask if they are suitable or unsuitable terms. In conclusion, I offer an analysis of why the distinction between these two terms matters as different ways to describe change-over-time and assess an alternative model to analyse and discuss these changes called ‘digital extension services.’ 

Reflexive Background and Context 

To set the background and context, let me write reflexively about why I am writing this paper. Over the past 15+ years studying the topic, I’ve become somewhat of an expert on how the term ‘evolution’ is used outside of the natural-physical sciences, in theories such as ‘social and cultural evolution,’ ‘evolutionary economics’ and ‘technological evolution.’

I wrote a master’s thesis comparing the concepts of ‘evolution,’ ‘extension’ and ‘Intelligent Design,’ and have published more than 20 papers and delivered more than 30 presentations at international conferences outlining and exploring the limits of ‘evolutionary’ thinking as well as promoting the notion of ‘human extension’ in social sciences and humanities[2].

My interest in this paper is to clear up what appears as massive public confusion and oftentimes puzzling equivocation about various types of change-over-time, especially non-evolutionary changes such as revolution, development, emergence, and extension. Some people think there is no such thing as a ‘non-evolutionary’ change since all change must be ‘evolutionary,’ in response to which I would like to set the record straight.

There are undoubtedly some people who will consider this paper and having written it to be a complete waste of time and for them, it’s best to stop reading at the end of this sentence. However, others may find in this exploration a key distinction towards gaining even a small bit of insight and perhaps some understanding into the considerable differences between biological change-over-time and technological development[3], innovation and planning, the latter which generally fall outside of the meaning of ‘evolution.’

Notably, I find it somewhat humorous for having studied this rather arcane social epistemological topic quite closely for many years to be able to write this paper now. It’s meant that I’ve had to lock horns repeatedly with ideological (young earth) creationists, Intelligent Design advocates and evolutionists on many occasions along the way[4]. What I have discovered is that sometimes choosing the right term matters and sometimes it doesn’t; some people want to use a term to mean whatever they want it to mean[5] and it’s most often not worth taking the time in trying to stop or persuade them.

When I learned in 2016 that blockchain technology is about more than just cryptocurrency, and that it also has potentially significant and far-reaching implications for a variety of social, cultural and educational uses, it simply made sense to bring some of the knowledge I had gathered as an associate professor and researcher into my study of distributed ledgers, which is what leads to this text.

In Q3 2017, I asked and answered myself on Twitter as follows: “Is blockchain really evolving of its own accord? No.” I copied that message to the Managing Director of the Blockchain Research Institute (BRI) in Toronto, Hilary Carter, who I had met that summer at the Blockchain Government Forum in Ottawa. She replied: “Agreed! Evolution is a series of beneficial genetic accidents. Blockchain and the development of the community is entirely intentional.” (24 Sep 2017) That exchange happened after I had recently arrived in Yangon, Myanmar, first to teach, then to work as Director of Blockchain Innovation at an educational technology startup company. I had many new things and needs to focus on and didn’t think about it too much further at that time.

However, after returning to Canada in 2018, I later raised this topic again directly in conversation with Carter[6]. While she still stands behind the view that blockchain is indeed a revolutionary phenomenon and that its development is based upon the various intentions of its builders and creators, she also suggested that, “the blockchain ecosystem is [an] evolution,” that it is in a state of maturation, and that, “no one is controlling it.” It is the latter contention that I’d like to take up again now and ‘unpack’ during the course of this paper.

Carter’s view, to which I will return below, raises an important question about how blockchain was invented, as well as the way that blockchain ecosystem development is currently being planned and executed, and both how and why people are aiming for social scalability and public adoption. Also, it raises the question of what then counts as the ‘blockchain revolution’ that BRI founder Don Tapscott wrote a book about with his son Alex in 2016.

To me, Carter’s original comment that blockchain development is ‘entirely intentional’ is obviously correct and requires no further commentary for validation. However, it also signifies that there is at least some type of ‘control’ when it comes to actual blockchain technology building, even if the trajectory of distributed ledgers aren’t being controlled, nor are they entirely predictable, by any single person or company, anywhere in the world.

My prior research in sociology of science had shown that while the term ‘evolution’ is used by not a few people in a basic colloquial sense simply as a synonym for ‘change,’ it can also be used, and not rarely, in an ideological sense that draws on ‘cultural evolutionary’ theories in SSH or in the case of technology, one that adheres to the so-called ‘laws of software evolution[7]‘ (M. Lehman). It is the latter usage of the term ‘evolution’ that I wholeheartedly reject and think has caused great damage to human self-understanding and initiative.

Let it be clear, however, in stating this that I am not one of the ‘new evolution deniers’ (Wright 2018) pursuing an anti-biology or anti-science blank slate ideology that doesn’t acknowledge change-over-time, which is evident in many ways across a range of cultural issues. Rather, I’m a dedicated social scientific researcher and more recently community builder of blockchain technology who rejects the notion that ‘no one is in control’ of what is being developed (i.e. ‘unguided evolution’).

Likewise, I strongly reject the misanthropic worldview that claims ‘there is no purpose[8]‘ (Dawkins) in change-over-time. I oppose both of these positions as dehumanising. So, with this context provided, the following sections present my research findings into how other people use the terms ‘evolution’ and ‘revolution’ with respect to blockchain technology.

Equivocating Between Evolution and Revolution 

“Bitcoin is a completely new narrative. It alters everything, and in 20 to 30 years from now, people will not recognise the world we are in because of Bitcoin.” – Craig Steven Wright (2019a)

Many writers on the topic of blockchain switch back and forth equivocally between ‘evolution’ and ‘revolution,’ apparently without much rhyme or reason, not carefully distinguishing between them. Rather curiously, this includes the Tapscotts. “We strongly believe that India has the potential to lead the blockchain revolution[9],” said Don Tapscott in 2018.

And there are indeed many places where Don and his son Alex use the term ‘revolution’ to describe blockchain in their 2016 book, which I will outline in the following paragraphs. They write, “Like the first generation of the Internet, the Blockchain Revolution promises to upend business models and transform industries. But that is just the start. Blockchain technology is pushing us inexorably into a new era, predicated on openness, merit, decentralization, and global participation.” (Ibid) This type of language continues throughout the book, which explains why they gave it the title they did.

However, they also use the term ‘evolution’ to describe technological change. “The Web is critical to the future of the digital world,” they say, “and all of us should support efforts under way to defend it, such as those of the World Wide Web Foundation, who are fighting to keep it open, neutral, and constantly evolving.” (Ibid)

They quote Blake Masters, who states, “Bear in mind that financial services infrastructures have not evolved in decades. The front end has evolved but not the back end. … posttrade infrastructure hasn’t really evolved at all.” (Ibid) Likewise, they cite Joseph Lubin, who says:

“I am not concerned about machine intelligence. We will evolve with it and for a long time it will be in the service of, or an aspect of, Homo sapiens cybernetica. It may evolve beyond us but that is fine. If so, it will occupy a different ecological niche. It will operate at different speeds and different relevant time scales. In that context, artificial intelligence will not distinguish between humans, a rock, or a geological process. We evolved past lots of species, many of which are doing fine (in their present forms).” (Ibid)

The Tapscotts in this vein also consider human-made technology itself, not just biology, as an ‘evolutionary’ phenomenon. They thus label one of their chapters, “The Evolution of Computing: from mainframes to smart pills.” (Ibid) “Unlike our energy grid,” they say, “computing power has evolved through several paradigms. In the 1950s and 1960s, mainframes ruled—International Business Machines and the Wild ‘BUNCH’ (Burroughs, Univac, National Cash Register Corp., Control Data, and Honeywell).

In the 1970s and 1980s, minicomputers exploded onto the scene.” (Ibid) They continue this line of thinking, suggesting that, “Driven by the same technological advances, communications networks evolved, too. From the early 1970s, the Internet (originating in the U.S. Advanced Research Projects Agency Network) was evolving into its present-day, worldwide, distributed network that connects more than 3.2 billion people, businesses, governments, and other institutions. The computing and networking technologies then converged in mobile tablets and handhelds. BlackBerry commercialized the smart phone in the early aughts, and Apple popularized it in the iPhone in 2007.” (Ibid)

Yet at some point unstated, they switch back to ‘revolutionary’ language, suggesting that, “We’re beginning the next major phase of the digital revolution.” (Ibid) They cite Michelle Tinsley of Intel, who “explained why her company is deeply investigating the blockchain revolution: “When PCs became pervasive, the productivity rates went through the roof. We connected those PCs to a server, a data center, or the cloud, making it really cheap and easy for lean start-ups to get computer power at their fingertips, and we’re again seeing rapid innovation, new business models.”

Just imagine the potential of applying these capabilities across many types of businesses, many untouched by the Internet revolution.” (Ibid) In short, their view is that “the technology is always evolving and designs are ever improving.” (Ibid) This encapsulates their equivocating meaning of ‘blockchain revolution,’ from one of the most widely cited texts in the field of blockchain technology.

Carter followed up with me after receiving the first draft of this paper to clarify her position. She explains, “We’ve evolved from single-purpose peer to peer electronic cash to Ethereum to private distributed ledgers to Cryptokitties. Everything is intentional. Evolution post-Bitcoin is more a figure of speech to reflect that blockchain systems have changed[10].” She continues, saying that, “Blockchain was no accidental software that emerged from the first generation of the internet.”

This sentence brings in another ‘change-over-time’ term with the notion of ’emergence,’ that adds to the linguistic feature of this analysis. Carter concludes that, “maybe ‘matured’ is a better word [i.e. than ‘evolution’] – because of the creativity of humans, not because of fortunate digital coincidences.” This explanation from the current leadership of the BRI helps to make sense of the variety of ways that people around the world are now speaking about the ‘growth,’ ’emergence,’ ‘maturing,’ ‘development,’ ‘advancement,’ ‘expansion’ and other ‘change-over-time’ metaphors to describe what is happening with distributed ledger technologies.

But What Are the Meanings of These Words?

Moving on to another writer and public figure, managing director of the IMF, Christine Lagarde similarly switches back and forth between ‘evolution’ and ‘revolution’ in seemingly an unsystematic way. She confirms that, “the fintech revolution questions the two forms of money we just discussed—coins and commercial bank deposits. And it questions the role of the state in providing money.” (2018)

She continues, however, saying, “I have tried to evaluate the case this morning for digital currency. The case is based on new and evolving requirements for money, as well as essential public policy objectives. My message is that while the case for digital currency is not universal, we should investigate it further, seriously, carefully, and creatively.” (Ibid)

One of the most prolific speakers and writers about blockchain, Andreas Antonopolous (2017), believes, “Over time, the way transaction fees are calculated and the effect they have on transaction prioritization has evolved. At first, transaction fees were fixed and constant across the network. Gradually, the fee structure relaxed and may be influenced by market forces, based on network capacity and transaction volume.” (2017: 127) … “Beyond bitcoin, the largest and most successful application of P2P technologies is file sharing, with Napster as the pioneer and BitTorrent as the most recent evolution of the architecture.” (Ibid: 171) He states that,

“the bitcoin network and software are constantly evolving, so consensus attacks would be met with immediate countermeasures by the bitcoin community, making bitcoin hardier, stealthier, and more robust than ever. … In order to evolve and develop the bitcoin system, the rules have to change from time to time to accommodate new features, improvements, or bug fixes. Unlike traditional software development, however, upgrades to a consensus system are much more difficult and require coordination between all the participants.” (Ibid: 256)

Further, he argues that, “Consensus software development continues to evolve and there is much discussion on the various mechanisms for changing the consensus rules.” (Ibid: 266) We thus see a major focus on ‘evolutionary’ blockchain change.

Yet in the final paragraph of the book, Antonopolous says, “We have examined just a few of the emerging applications that can be built using the bitcoin blockchain as a trust platform. These applications expand the scope of bitcoin beyond payments and beyond financial instruments, to encompass many other applications where trust is critical. By decentralizing the basis of trust, the bitcoin blockchain is a platform that will spawn many revolutionary applications in a wide variety of industries.” (Ibid: 304) The future of blockchain, therefore might be revolutionary based on many ‘evolutions’ of the technology.

In Life after Google: the Fall of Big Data and the Rise of the Blockchain Economy, George Gilder flip-flops back and forth between evolution and revolution with little apparent consistency, speaking about “the root-and-branch revolution of distributed peer-to-peer technology, which I call the ‘cryptocosm’,” (2018: 44) then stating that, “[t]he next wave of innovation will compress today’s parallel solutions in an evolutionary convergence of electronics and optics.” (Ibid: 58)

He suggests that, “[a] decentralized and open global rendering system is foundational for disruptive services and platforms to evolve from the post-mobile world of immersive computing, just as the open web was formed in the creation of Google, Amazon and Facebook.” (Ibid: 205) However, he also notes that, “Far beyond mere high-definition voice, 5G is the technological infrastructure for a coming revolution in networks. It enables new distributed security systems for the Internet of Things, the blockchain ledgers of the new crypto-economy of micropayments, and the augmented and virtual reality platforms of advanced Internet communications.” (Ibid: 231)

Gilder’s language seems to sometimes be more about appearance than substance, as he writes, “In the evolving technological economy, shaped by cryptographic innovations, Google is going to have to compete again.” (Ibid: 239) Further explaining, he notes that, “The revolution in cryptography has caused a great unbundling of the roles of money, promising to reverse the doldrums of the Google Age, which has been an epoch of bundling together, aggregating, all the digital assets of the world.” (Ibid: 256)

One key formulation renders his ideological views visible, reflecting his affiliation with the Discovery Institute: “The new system of the world must reverse these positions, exalting the singularities of creation: mind over matter, human consciousness over mechanism, real intelligence over mere algorithmic search, purposeful learning over mindless evolution, and truth over chance. A new system can open a heroic age of human accomplishment.” (Ibid: 272) Gilder seems to have no difficulty both denying and accepting ‘evolution’ at the same time, regardless of the fact that everyone agrees both ‘minds’ and ‘matter’ are involved in developing technologies.

Uncertainty Too From Financial Technology Leaders

Hanna Halaburda writes for the Bank of Canada (2018), saying, “The market’s excitement about blockchain technologies is growing and is perhaps best summarized in the increasingly popular slogan ‘blockchain revolution.’ It is estimated that the blockchain market size will grow from US$210 million in 2016 to over US$2 billion by 2021.” (2018: 1) Later in the paper she uses both terms, suggesting that,

“The broadening of the meaning of ‘blockchain’ to include smart contracts, encryption and distributed ledger could simply reflect the evolution of a term in a living language. However, precision matters for estimating costs and benefits, or even for predicting the best uses of blockchain technologies. Smart contracts, encryption and distributed ledger each bring different benefits. And since they can be implemented independently, an optimal solution for a particular application may include only some of these tools but not others. This may matter for the future of the blockchain revolution.” (Ibid: 5)

In conclusion, she accepts the same terminology as the Tapscotts, saying, “The blockchain revolution has brought distributed databases to the forefront and may result in wider adoption and new ideas for their use.” (Ibid: 9)

Andrea Pinna and Weibe Ruttenberg (2016) write that, “Over the last decade, information technology has contributed significantly to the evolution of financial markets, without, however, revolutionising the way in which financial institutions interact with one another. This may be about to change, as some market players are now predicting that new database technologies, such as blockchain and other distributed ledger technologies (DLTs), could be the source of an imminent revolution.” (Ibid: 2) “It is not yet, therefore, clear whether DLTs will cause a major revolution in mainstream financial markets or whether their use will remain limited to particular niches.” (Ibid: 32)

Former Chief Scientific Advisor to the British Government, Mark Walport (2016) suggests, “The development of block chain technology is but the first, though very important step towards a disruptive revolution in ledger technology that could transform the conduct of public and private sector organisations.” (2016: 10) He continues, “Regulation will need to evolve in parallel with the development of new implementations and applications of the technology” (Ibid: 12)

However, he also distinguishes a ‘revolutionary’ dimension to the technology, saying, “We are still at the early stages of an extraordinary post-industrial revolution driven by information technology. It is a revolution [that] is bringing important new benefits and risks. It is already clear that, within this revolution, the advent of distributed ledger technologies is starting to disrupt many of the existing ways of doing business.” (Ibid: 16)

And then he reverts back to evolutionary language, saying, “The terminology of this new field is still evolving, with many using the terms block chain (or blockchain), distributed ledger and shared ledger interchangeably.” (Ibid: 17) He emphasizes that, “M-Pesa challenged the notion that value transfer for exchange transactions had to be done through banks, and leapfrogged several developmental stages. But these innovations still rely on an existing hierarchical structure, using proprietary technology and trusted intermediaries. Though the change improves customer convenience, and significantly reduces costs to users and customers, this is evolution rather than revolution.” (Ibid: 54) Walport is one of the few voices insisting that changes in blockchain development are happening at a rather slower than rapid pace, which seems to determine his choice of terms.

Sam Town makes clear his preferred terminology between the two notions, stating, “While the ICO as it exists today may be gone tomorrow, the blockchain brings evolution, not revolution.” (2018) Here he seems to be suggesting that while ICOs may not last long as a credible method of fundraising, at least not without more stringent regulatory oversight, that nevertheless blockchain distributed ledger technologies will indeed have lasting and significant impact on finance and economics.

Does Evolution vs Revolution Matter?

Ugur Demirbas et al. (2018) also write to intentionally distinguish the two terms, saying, “In summary, while digital transformation shows disruptive influence on individual elements, its overall effect is rather evolutionary than revolutionary. The impact of DT in the context of the overarching corporate sourcing strategy is an incremental change than a disruptive creation of something completely new.” (2018: 8)

Again we see an explanation given that ‘evolutionary’ is preferred because of the pace (slow) and type (incremental) of change or the people’s aims and goals involved in developing the technology. They also indicate ‘disruption’ and ‘something completely new’ in their meaning of ‘revolutionary,’ which we will look at again below.

Jagjit Dhaliwal (2018) says that, “We all know that the Blockchain technology is revolutionizing our future by providing distributed networks, allowing peer-to-peer transactions without intermediaries. We have come a long way in a really short period of time from the inception of Bitcoin, one of the first cryptocurrencies based on Blockchain technology.”

He continues saying that, “Everyone is curious about which platform and cryptocurrency will win the race. The DLT landscape is changing rapidly and evolving really fast. I won’t be surprised if some of the solutions in this article will [sic] extinct soon.” Dhaliwal thus likewise shows that the pace of change impacts his choice of terms, though it is unclear how ‘rapid change’ and ‘fast evolution’ differ from ‘revolutionary.’

In a paper curiously named “The Evolution of Blockchain Development” (2017), the team at Alibaba Cloud similarly suggests that, “Blockchain as a technology has evolved rapidly in the past decade.” They continue, however, by appealing to readers: “Let us discuss a few major innovations that have revolutionized this field[11].” This is yet another example of the confusion in using the terms ‘evolution’ and ‘revolution’ when there is no clear explanation of what differentiates one from the other.

Megan Ray Nichols weighs in on the ‘revolution’ side, when she says, “blockchain is serving as a critical component in a major revolution that also includes rapid prototyping, lean manufacturing, 3D printing, & now blockchain-facilitated manufacturing & supply contracts.” (2018).

This and several of the examples above certainly do not refer to a ‘political revolution’ or ‘scientific revolution,’ but rather to an incoming ‘technological revolution’ that is supposedly happening all around us with ’emergent’ or ‘nascent’ new technologies, including, but not exclusive to blockchain. The hype surrounding blockchain with expectations in the near future, however, often seems to far exceed evidence of what has changed so far because of it.

Don Tapcott responded in an interview with McKinsey that, “the blockchain, the underlying technology, is the biggest innovation in computer science—the idea of a distributed database where trust is established through mass collaboration and clever code rather than through a powerful institution that does the authentication and the settlement[12].”

We have, of course, heard this kind of suggestive language before, so it’s not like predictions about ‘revolutionary technology’ are entirely new. One example of this harkens back to what Fred Brooks asked in 1975, if “technical developments that are most often advanced as potential silver bullets … offer revolutionary advances, or incremental ones?” (1975: 188) While not a few people have expressed inflated expectations for distributed ledger systems, we are still nevertheless waiting for a clear example of widespread usage of blockchain to be able to assess the variable speeds at which adoption can and likely will eventually take place.

With that basic background, we will now look at largely colloquial uses of the term ‘evolution’ as it relates to blockchain technology development.

Colloquial Usage of ‘Evolution’ for Blockchain Technology Development

A remarkable pattern among technology writers is to apply the term ‘evolution’ in what appears to be a basic colloquial way, suggesting no theoretical underpinning or technical meaning, and with no ideological implications. Instead, for these cases, the notion of ‘evolution’ is basically just used as a synonym for either ‘change’ (i.e. over time), ‘development,’ ‘creation’ or some kind of a general ‘process of history.’

Brigid McDermott, vice president of IBM blockchain business development, states:

“We’re asking companies to join to help evolve the solution and guide and steer its direction.”

“We’ll do PoCs [proofs-of-concept] later down the line.[1]” In this case, the verb ‘to evolve’ is meant in the same way as ‘to create,’ ‘to build’ or ‘to develop,’ without the notion of a natural genetic population, implication of a ‘struggle for life’ or ‘survival of the fittest,’ rates of mutation, variation, or other notions usually connected with ‘biological evolutionary theory.”

The Commonwealth of Learning suggests that, “When it comes to educational innovation, blockchains and ledgers are likely to lead to evolutionary gains[2].” While it is not entirely clear what they mean in this short report, we are likely supposed to gather a sense of ‘progress’ or ‘advancement’ in what they imply and suggest blockchain will lead to in the field of education.

Margaret Leigh Sinrod writes about blockchain for the World Economic Forum (2018). “The fact that banks are investing in this [blockchain] technology may sound fairly paradoxical,” she says, “given the context in which it evolved and gained traction.” In this case, the term ‘evolved’ seems to simply signify ‘history,’ i.e. that ‘something has happened’ and that blockchain now continues to persist as a phenomenon.

Dennis Sahlstrom similarly tells us that, “the evolution of blockchain arrived with Ethereum, created by Vitalik Buterin, which was an improvement of Bitcoin. This evolution added a further element which is the ability to build decentralized applications (dApps) and smart contracts to ensure that deals, transactions, and many other tasks can be performed without intermediaries.” (2018)

Here we see ‘evolution’ used as a way to symbolise a historical fact, again that ‘something has happened,’ thus indicating a new ‘stage’ of blockchain that also was ‘created. This approach might be confusing to people who accept a more technical meaning of ‘evolution’ as distinct from ‘creation’ or ‘intentional planning,’ almost sounding as if blockchain has taken on a life of its own.

John Dean Markunas from Power of Chain Consultancy continues this anthropomorphic language, suggesting that, “The [blockchain] technology itself will continue to evolve along with a wide variety of creative applications developed on top of it, similar to the development of the internet and world-wide-web[3].” This usage, while it signifies persistence and continuity, appears particularly confusing since the term ‘development’ is also used referring to the Internet, which other people claim has led to a ‘revolution’ in human society, as seen above.

Tadas Deksnys CEO and Founder of Unboxed writes that, “Though the future of ICOs is vague, the blockchain industry is still evolving and presenting new opportunities[4].” Again, we see here the notion of both history and continuity and that there is some kind of on-going process of unspecified speed, type or significance.

These are all common examples of people involved in or writing about the blockchain industry who suggest that blockchain demonstrates an ‘evolutionary’ rather than a ‘revolutionary,’ ‘developmental’ or otherwise ‘non-evolutionary’ process of change-over-time.

Frederik De Breuck (2019) says that, “its capabilities and platforms (both public and private) are rapidly evolving and blockchain and distributed ledgers remain for me (and many others) two of the most promising technology evolutions of recent decades for their potential to transform both society and enterprises.”

He uses other change-based concepts as well, such as emergence and extension, in the latter case saying, “[w]e think next year will see the ongoing evolution of these complex trust architectures and their extension beyond their organizational boundaries, into both ecosystems and society.” (Ibid) This language basically indicates something supposedly important is happening with blockchain, a description that it is growing and reaching more people in a community, network and/or ecosystem.

Reflections of What May Be Historical Precedents

Jesus Leal Trujilo et al. in their Deloitte paper (2017) base their logic in the ‘evolution’ of digital ecosystems, writing, “Our study appears to be the first empirical attempt to understand the evolution of blockchain using metadata available on GitHub … Our findings could help firms improve their ability to identify successful projects and opportunities based on how the blockchain ecosystem is evolving.” (2017: 2)

They also address the time period in terms of stages of development, saying, “At the current evolutionary stage of blockchain technology, it is likely to be in a developer’s best interest to develop, or watch the development of, blockchain solutions on open source. Blockchain appears to have a better chance to more quickly achieve rigorous protocols and standardization through open-source collaboration, which could make developing permissioned blockchains easier and better.” (Ibid: 5)

They continue, “The data scientists of Deloitte developed and honed a methodology to analyze and organize GitHub data in order to better understand the evolution of a young, possibly transformative technology and its ecosystem.” (Ibid: 15) They conclude saying, “It is our hope that these findings can arm the financial services industry with the data it may need to not only better identify successful projects and opportunities based on how the blockchain ecosystem is evolving, but to become influential participants, themselves, in how blockchain evolves.” (Ibid: 15) Thus, the promote both the development and so-called ‘evolution’ of blockchain technology based on the language of ‘ecosystem’ that loosely mimics biology.

The Systems Academy suggests about blockchain technology that, “over the past years it has been evolving fast, from the original Bitcoin protocol to the second generation Ethereum platform, to today where we are in the process of building what some call blockchain 3.0. In this evolution we can see how the technology is evolving from its initial form as essentially just a database, to becoming a fully-fledged globally distributed cloud computer.”

They add to others in this paper who suggest that, “The development and adoption of the Ethereum platform was a major step forward in the evolution of blockchain technology[5],” suggesting a kind of ‘progress’ narrative that switches between ‘development’ and ‘evolution’ and indicates improvement rather than replacement or destruction of the old system.

Stapels et al. flip back and forth between ‘development’ and ‘evolution,’ stating that, “blockchains are still a rapidly evolving technology, with ongoing developments, especially to improve scalability and confidentiality. Globally, governments, enterprises, and startups are exploring the technology/market fit in a wide variety of use cases and for a wide variety of requirements and regulatory demands.” They also suggest a present lack of knowledge towards building and maintaining trust among blockchain users, saying “There is still much that is unknown about the development of trustworthy blockchain-based systems.” (2018: 1)

Bryan Zhang writes in the Foreword to Rauchs et al. 2018, that, “the landscape of DLT itself continues its swift evolution.” Again, we see the suggestion of a continuity of some kind, as if we are in a historical period of flux and change with the rise of DLTs. In conclusion, the authors state that, “Nearly 10 years after Bitcoin entered the world, the DLT ecosystem is still in early stages: it is constantly evolving and characterised by relentless experimentation and R&D.” (2018: 92)

This usage doesn’t necessarily imply that Bitcoin arrived on its own without a creative inventor or network of users, but rather that it’s simply in a process that has yet to reach its conclusion and thus should be thought of as impermanent or temporary.

ElBarhrawy et al. (2017) “Here, we present a first complete analysis of the cryptocurrency market, considering its evolution between April 2013 and May 2017.” (Ibid: 2) They then suggest there is a theoretical underpinning one can use to study this historical period involving cryptocurrencies. “By adopting an ecological perspective, we have pointed out that the neutral model of evolution captures several of the observed properties of the market.” (Ibid: 7)

In this approach we again see usage of the term ‘evolution’ to mean ‘history,’ yet in a broader way that combines economics with ecology and push the idea of ‘ecosystem’ thinking that is also front and centre in much of the ideological blockchain evolutionism below.

Contact details: gregory.sandstrom@gmailcom

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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] Nov. 14, 2008. https://satoshi.nakamotoinstitute.org/emails/cryptography/12/

[2] Your author of this paper received his degree in ‘Sociological Sciences’ from St. Petersburg State University in Russia, after a dissertation defense at the Sociological Institute of the Russian Academy of Science in 2010.

[3] “The gap between biological evolution and artificial systems evolution is just too enormous to expect to link the two.” – Meir Lehman (In Williams, 2002)

[4] It is most likely that none of the authors cited in this study was thinking about ‘young earth creationism’ as a position that they aimed to oppose by using the term ‘evolution.’ Similarly, no theory of ‘Intelligent Design’ as an alternative to ‘neo-Darwinism’ is at the heart of this paper’s rejection of ‘technological evolutionary’ theories.

[5] “When I use a word,” Humpty Dumpty said, in rather a scornful tone, “it means just what I choose it to mean—neither more nor less.” – Lewis Carroll (Through the Looking-Glass, 1872)

[6] Private conversation 07-02-2019.

[7] “In software engineering there is no theory. It’s all arm flapping and intuition. I believe that a theory of software evolution could eventually translate into a theory of software engineering. Either that or it will come very close. It will lay the foundation for a wider theory of software evolution.” – Lehman (In Williams 2002)

[8] “This is one of the hardest lessons for humans to learn. We cannot admit that things might be neither good nor evil, neither cruel nor kind, but simply callous – indifferent to all suffering, lacking all purpose.” … “The universe we observe has precisely the properties we should expect if there is, at bottom, no design, no purpose, no evil and no good, nothing but blind pitiless indifference.” – Richard Dawkins (River Out of Eden. Basic Books, New York, 1995: 95)

[9] https://money.cnn.com/2018/02/21/technology/canada-india-blockchain-partnership-bri-nasscom/index.html

[10] Private email, 24-02-2019.

[11] https://www.alibabacloud.com/blog/The-Evolution-of-Blockchain-Development_p73812

[12] http://www.mckinsey.com/industries/high-tech/our-insights/how-blockchains-could-change-the-world

[1] http://fortune.com/2017/08/22/walmart-blockchain-ibm-food-nestle-unilever-tyson-dole/

[2] https://www.col.org/news/news/col-promotes-blockchain-education

[3] https://www.linkedin.com/pulse/emancipation-from-ball-chain-blockchain-john-dean-markunas

[4] https://medium.com/unboxed-network/our-journey-so-far-unboxed-airdrop-update-72b63ab52631

[5] http://complexitylabs.io/evolution-of-blockchain/

Author Information: Brian Martin, University of Wollongong, bmartin@uow.edu.au.

Martin, Brian. “Bad Social Science.” Social Epistemology Review and Reply Collective 8, no. 3 (2019): 6-16.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-47a

Image by Sanofi Pasteur via Flickr / Creative Commons

 

People untrained in social science frameworks and methods often make assumptions, observations or conclusions about the social world.[1] For example, they might say, “President Trump is a psychopath,” thereby making a judgement about Trump’s mental state. The point here is not whether this judgement is right or wrong, but whether it is based on a careful study of Trump’s thoughts and behaviour drawing on relevant expertise.

In most cases, the claim “President Trump is a psychopath” is bad psychology, in the sense that it is a conclusion reached without the application of skills in psychological diagnosis expected among professional psychologists and psychiatrists.[2] Even a non-psychologist can recognise cruder forms of bad psychology: they lack the application of standard tools in the field, such as comparison of criteria for psychopathy with Trump’s thought and behaviour.

“Bad social science” here refers to claims about society and social relationships that fall very far short of what social scientists consider good scholarship. This might be due to using false or misleading evidence, making faulty arguments, drawing unsupported conclusions or various other severe methodological, empirical or theoretical deficiencies.

In all sorts of public commentary and private conversations, examples of bad social science are legion. Instances are so common that it may seem pointless to take note of problems with ill-informed claims. However, there is value in a more systematic examination of different sorts of everyday bad social science. Such an examination can point to what is important in doing good social science and to weaknesses in assumptions, evidence and argumentation. It can also provide insights into how to defend and promote high-quality social analysis.

Here, I illustrate several facets of bad social science found in a specific public scientific controversy: the Australian vaccination debate. It is a public debate in which many partisans make claims about social dynamics, so there is ample material for analysis. In addition, because the debate is highly polarised, involves strong emotions and is extremely rancorous, it is to be expected that many deviations from calm, rational, polite discourse would be on display.

Another reason for selecting this topic is that I have been studying the debate for quite a number of years, and indeed have been drawn into the debate as a “captive of controversy.”[3] Several of the types of bad social science are found on both sides of the debate. Here, I focus mainly on pro-vaccination campaigners for reasons that will become clear.

In the following sections, I address several facets of bad social science: ad hominem attacks, not defining terms, use of limited and dubious evidence, misrepresentation, lack of reference to alternative viewpoints, lack of quality control, and drawing of unjustified conclusions. In each case, I provide examples from the Australian public vaccination debate, drawing on my experience. In a sense, selecting these topics represents an informal application of grounded theory: each of the shortcomings became evident to me through encountering numerous instances. After this, I note that there is a greater risk of deficient argumentation when defending orthodoxy.

With this background, I outline how studying bad social science can be of benefit in three ways: as a pointer to particular areas in which it is important to maintain high standards, as a toolkit for responding to attacks on social science, and as a reminder of the need to improve public understanding of social science approaches.

Ad Hominem

In the Australian vaccination debate, many partisans make adverse comments about opponents as a means of discrediting them. Social scientists recognise that ad hominem argumentation, namely attacking the person rather than dealing with what they say, is illegitimate for the purposes of making a case.

In the mid 1990s, Meryl Dorey founded the Australian Vaccination Network (AVN), which became the leading citizens’ group critical of government vaccination policy.[4] In 2009, a pro-vaccination citizens’ group called Stop the Australian Vaccination Network (SAVN) was set up with the stated aim of discrediting and shutting down the AVN.[5] SAVNers referred to Dorey with a wide range of epithets, for example “cunt.”[6]

What is interesting here is that some ad hominem attacks contain an implicit social analysis. One of them is “liar.” SAVNer Ken McLeod accused Dorey of being a liar, giving various examples.[7] However, some of these examples show only that Dorey persisted in making claims that SAVNers believed had been refuted.[8] This does not necessarily constitute lying, if lying is defined, as it often is by researchers in the area, as consciously intending to deceive.[9] To the extent that McLeod failed to relate his claims to research in the field, his application of the label “liar” constitutes bad social science.

Another term applied to vaccine critics is “babykiller.” In the Australian context, this word contains an implied social analysis, based on these premises: public questioning of vaccination policy causes some parents not to have their children vaccinated, leading to reduced vaccination rates and thence to more children dying of infectious diseases.

“Babykiller” also contains a moral judgement, namely that public critics of vaccination are culpable for the deaths of children from vaccination-preventable diseases. Few of those applying the term “babykiller” provide evidence to back up the implicit social analysis and judgement, so the label in these instances represents bad social science.

There are numerous other examples of ad hominem in the vaccination debate, on both sides. Some of them might be said to be primarily abuse, such as “cunt.” Others, though, contain an associated or implied social analysis, so to judge its quality it is necessary to assess whether the analysis conforms to conventions within social science.

Undefined terms

In social science, it is normal to define key concepts, either by explicit definitions or descriptive accounts. The point is to provide clarity when the concept is used.

One of the terms used by vaccination supporters in the Australian debate is “anti-vaxxer.” Despite the ubiquity of this term in social and mass media, I have never seen it defined. This is significant because of the considerable ambiguity involved. “Anti-vaxxer” might refer to parents who refuse all vaccines for their children and themselves, parents who have their children receive some but not all recommended vaccines, parents who express reservations about vaccination, and/or campaigners who criticise vaccination policy.

The way “anti-vaxxer” is applied in practice tends to conflate these different meanings, with the implication that any criticism of vaccination puts you in the camp of those who refuse all vaccines. The label “anti-vaxxer” has been applied to me even though I do not have a strong view about vaccination.[10]

Because of the lack of a definition or clear meaning, the term “anti-vaxxer” is a form of ad hominem and also represents bad social science. Tellingly, few social scientists studying the vaccination issue use the term descriptively.

In their publications, social scientists may not define all the terms they use because their meanings are commonly accepted in the field. Nearly always, though, some researchers pay close attention to any widely used concept.[11] When such a concept remains ill-defined, this may be a sign of bad social science — especially when it is used as a pejorative label.

Limited and Dubious Evidence

Social scientists normally seek to provide strong evidence for their claims and restrict their claims to what the evidence can support. In public debates, this caution is often disregarded.

After SAVN was formed in 2009, one of its initial claims was that the AVN believed in a global conspiracy to implant mind-control chips via vaccinations. The key piece of evidence SAVNers provided to support this claim was that Meryl Dorey had given a link to the website of David Icke, who was known to have some weird beliefs, such as that the world is ruled by shape-shifting reptilian humanoids.

The weakness of this evidence should be apparent. Just because Icke has some weird beliefs does not mean every document on his website involves adherence to weird beliefs, and just because Dorey provided a link to a document does not prove she believes in everything in the document, much less subscribes to the beliefs of the owner of the website. Furthermore, Dorey denied believing in a mind-control global conspiracy.

Finally, even if Dorey had believed in this conspiracy, this does not mean other members of the AVN, or the AVN as an organisation, believed in the conspiracy. Although the evidence was exceedingly weak, several SAVNers, after I confronted them on the matter, initially refused to back down from their claims.[12]

Misrepresentation

When studying an issue, scholars assume that evidence, sources and other material should be represented fairly. For example, a quotation from an author should fairly present the author’s views, and not be used out of context to show something different than what the author intended.

Quite a few campaigners in the Australian vaccination debate use a different approach, which might be called “gotcha”. Quotes are used to expose writers as incompetent, misguided or deluded. Views of authors are misrepresented as a means of discrediting and dismissing them.

Judy Wilyman did her PhD under my supervision and was the subject of attack for years before she graduated. On 13 January 2016, just two days after her thesis was posted online, it was the subject of a front-page story in the daily newspaper The Australian. The journalist, despite having been informed of a convenient summary of the thesis, did not mention any of its key ideas, instead claiming that it involved a conspiracy theory. Quotes from the thesis, taken out of context, were paraded as evidence of inadequacy.

This journalistic misrepresentation of Judy’s thesis was remarkably influential. It led to a cascade of hostile commentary, with hundreds of online comments on the numerous stories in The Australian, an online petition signed by thousands of people, and calls by scientists for Judy’s PhD to be revoked. In all the furore, not a single critic of her thesis posted a fair-minded summary of its contents.[13]

Alternative Viewpoints?

In high-quality social science, it is common to defend a viewpoint, but considered appropriate to examine other perspectives. Indeed, when presenting a critique, it is usual to begin with a summary of the work to be criticised.

In the Australian vaccination debate, partisans do not even attempt to present the opposing side’s viewpoint. I have never seen any campaigner provide a summary of the evidence and arguments supporting the opposition’s viewpoint. Vaccination critics present evidence and arguments that cast doubt on the government’s vaccination policy, and never try to summarise the evidence and arguments supporting it. Likewise, backers of the government’s policy never try to summarise the case against it.

There are also some intermediate viewpoints, divergent from the entrenched positions in the public debate. For example, there are some commentators who support some vaccines but not all the government-recommended ones, or who support single vaccines rather than multiple vaccines. These non-standard positions are hardly ever discussed in public by pro-vaccination campaigners.[14] More commonly, they are implicitly subsumed by the label “anti-vaxxer.”

To find summaries of arguments and evidence on both sides, it is necessary to turn to work by social scientists, and then only the few of them studying the debate without arguing for one side or the other.[15]

Quality Control

When making a claim, it makes sense to check it. Social scientists commonly do this by checking sources and/or by relying on peer review. For contemporary issues, it’s often possible to check with the person who made the claim.

In the Australian vaccination debate, there seems to be little attempt to check claims, especially when they are derogatory claims about opponents. I can speak from personal experience. Quite a number of SAVNers have made comments about my work, for example in blogs. On not a single occasion has any one of them checked with me in advance of publication.

After SAVN was formed and I started writing about free speech in the Australian vaccination debate, I sent drafts of some of my papers to SAVNers for comment. Rather than using this opportunity to send me corrections and comments, the response was to attack me, including by making complaints to my university.[16] Interestingly, the only SAVNer to have been helpful in commenting on drafts is another academic.

Another example concerns Andrew Wakefield, a gastroenterologist who was lead author of a paper in The Lancet suggesting that the possibility that the MMR triple vaccine (measles, mumps and rubella) might be linked to autism should be investigated. The paper led to a storm of media attention.

Australian pro-vaccination campaigns, and quite a few media reports, refer to Wakefield’s alleged wrongdoings, treating them as discrediting any criticism of vaccination. Incorrect statements about Wakefield are commonplace, for example that he lost his medical licence due to scientific fraud. It is a simple matter to check the facts, but apparently few do this. Even fewer take the trouble to look into the claims and counterclaims about Wakefield and qualify their statements accordingly.[17]

Drawing Conclusions

Social scientists are trained to be cautious in drawing conclusions, ensuring that they do not go beyond what can be justified from data and arguments. In addition, it is standard to include a discussion of limitations. This sort of caution is often absent in public debates.

SAVNers have claimed great success in their campaign against the AVN, giving evidence that, for example, their efforts have prevented AVN talks from being held and reduced media coverage of vaccine critics. However, although AVN operations have undoubtedly been hampered, this does not necessarily show that vaccination rates have increased or, more importantly, that public health has benefited.[18]

Defending Orthodoxy

Many social scientists undertake research in controversial areas. Some support the dominant views, some support an unorthodox position and quite a few try not to take a stand. There is no inherent problem in supporting the orthodox position, but doing so brings greater risks to the quality of research.

Many SAVNers assume that vaccination is a scientific issue and that only people with scientific credentials, for example degrees or publications in virology or epidemiology, have any credibility. This was apparent in an article by philosopher Patrick Stokes entitled “No, you’re not entitled to your opinion” that received high praise from SAVNers.[19] It was also apparent in the attack on Judy Wilyman, whose PhD was criticised because it was not in a scientific field, and because she analysed scientific claims without being a scientist. The claim that only scientists can validly criticise vaccination is easily countered.[20] The problem for SAVNers is that they are less likely to question assumptions precisely because they support the dominant viewpoint.

There is a fascinating aspect to campaigners supporting orthodoxy: they themselves frequently make claims about vaccination although they are not scientists with relevant qualifications. They do not apply their own strictures about necessary expertise to themselves. This can be explained as deriving from “honour by association,” a process parallel to guilt by association but less noticed because it is so common. In honour by association, a person gains or assumes greater credibility by being associated with a prestigious person, group or view.

Someone without special expertise who asserts a claim that supports orthodoxy implicitly takes on the mantle of the experts on the side of orthodoxy. It is only those who challenge orthodoxy who are expected to have relevant credentials. There is nothing inherently wrong with supporting the orthodox view, but it does mean there is less pressure to examine assumptions.

My initial example of bad social science was calling Donald Trump a psychopath. Suppose you said Trump has narcissistic personality disorder. This might not seem to be bad social science because it accords with the views of many psychologists. However, agreeing with orthodoxy, without accompanying deployment of expertise, does not constitute good social science any more than disagreeing with orthodoxy.

Lessons

It is all too easy to identify examples of bad social science in popular commentary. They are commonplace in political campaigning and in everyday conversations.

Being attuned to common violations of good practice has three potential benefits: as a useful reminder to maintain high standards; as a toolkit for responding to attacks on social science; and as a guide to encouraging greater public awareness of social scientific thinking and methods.

Bad Social Science as a Reminder to Maintain High Standards

Most of the kinds of bad social science prevalent in the Australian vaccination debate seldom receive extended attention in the social science literature. For example, the widely used and cited textbook Social Research Methods does not even mention ad hominem, presumably because avoiding it is so basic that it need not be discussed.

It describes five common errors in everyday thinking that social scientists should avoid: overgeneralisation, selective observation, premature closure, the halo effect and false consensus.[21] Some of these overlap with the shortcomings I’ve observed in the Australian vaccination debate. For example, the halo effect, in which prestigious sources are given more credibility, has affinities with honour by association.

The textbook The Craft of Research likewise does not mention ad hominem. In a final brief section on the ethics of research, there are a couple of points that can be applied to the vaccination debate. For example, ethical researchers “do not caricature or distort opposing views.” Another recommendation is that “When you acknowledge your readers’ alternative views, including their strongest objections and reservations,” you move towards more reliable knowledge and honour readers’ dignity.[22] Compared with the careful exposition of research methods in this and other texts, the shortcomings in public debates are seemingly so basic and obvious as to not warrant extended discussion.

No doubt many social scientists could point to the work of others in the field — or even their own — as failing to meet the highest standards. Looking at examples of bad social science can provide a reminder of what to avoid. For example, being aware of ad hominem argumentation can help in avoiding subtle denigration of authors and instead focusing entirely on their evidence and arguments. Being reminded of confirmation bias can encourage exploration of a greater diversity of viewpoints.

Malcolm Wright and Scott Armstrong examined 50 articles that cited a method in survey-based research that Armstrong had developed years earlier. They discovered that only one of the 50 studies had reported the method correctly. They recommend that researchers send drafts of their work to authors of cited studies — especially those on which the research depends most heavily — to ensure accuracy.[23] This is not a common practice in any field of scholarship but is worth considering in the interests of improving quality.

Bad Social Science as a Toolkit for Responding to Attacks

Alan Sokal wrote an intentionally incoherent article that was published in 1996 in the cultural studies journal Social Text. Numerous commentators lauded Sokal for carrying out an audacious prank that revealed the truth about cultural studies, namely that it was bunk. These commentators had not carried out relevant studies themselves, nor were most of them familiar with the field of cultural studies, including its frameworks, objects of study, methods of analysis, conclusions and exemplary pieces of scholarship.

To the extent that these commentators were uninformed about cultural studies yet willing to praise Sokal for his hoax, they were involved in a sort of bad social science. Perhaps they supported Sokal’s hoax because it agreed with their preconceived ideas, though investigation would be needed to assess this hypothesis.

Most responses to the hoax took a defensive line, for example arguing that Sokal’s conclusions were not justified. Only a few argued that interpreting the hoax as showing the vacuity of cultural studies was itself poor social science.[24] Sokal himself said it was inappropriate to draw general conclusions about cultural studies from the hoax,[25] so ironically it would have been possible to respond to attackers by quoting Sokal.

When social scientists come under attack, it can be useful to examine the evidence and methods used or cited by the attackers, and to point out, as is often the case, that they fail to measure up to standards in the field.

Encouraging Greater Public Awareness of Social Science Thinking and Methods

It is easy to communicate with like-minded scholars and commiserate about the ignorance of those who misunderstand or wilfully misrepresent social science. More challenging is to pay close attention to the characteristic ways in which people make assumptions and reason about the social world and how these ways often fall far short of the standards expected in scholarly circles.

By identifying common forms of bad social science, it may be possible to better design interventions into public discourse to encourage more rigorous thinking about evidence and argument, especially to counter spurious and ill-founded claims by partisans in public debates.

Conclusion

Social scientists, in looking at research contributions, usually focus on what is high quality: the deepest insights, the tightest arguments, the most comprehensive data, the most sophisticated analysis and the most elegant writing. This makes sense: top quality contributions offer worthwhile models to learn from and emulate.

Nevertheless, there is also a role for learning from poor quality contributions. It is instructive to look at public debates involving social issues in which people make judgements about the same sorts of matters that are investigated by social scientists, everything from criminal justice to social mores. Contributions to public debates can starkly show flaws in reasoning and the use of evidence. These flaws provide a useful reminder of things to avoid.

Observation of the Australian vaccination debate reveals several types of bad social science, including ad hominem attacks, failing to define terms, relying on dubious sources, failing to provide context, and not checking claims. The risk of succumbing to these shortcomings seems to be magnified when the orthodox viewpoint is being supported, because it is assumed to be correct and there is less likelihood of being held accountable by opponents.

There is something additional that social scientists can learn by studying contributions to public debates that have serious empirical and theoretical shortcomings. There are likely to be characteristic failures that occur repeatedly. These offer supplementary guidance for what to avoid. They also provide insight into what sort of training, for aspiring social scientists, is useful for moving from unreflective arguments to careful research.

There is also a challenge that few scholars have tackled. Given the prevalence of bad social science in many public debates, is it possible to intervene in these debates in a way that fosters greater appreciation for what is involved in good quality scholarship, and encourages campaigners to aspire to make sounder contributions?

Contact details: bmartin@uow.edu.au

References

Blume, Stuart. Immunization: How Vaccines Became Controversial. London: Reaktion Books, 2017.

Booth, Wayne C.; Gregory G. Colomb, Joseph M. Williams, Joseph Bizup and William T. FitzGerald, The Craft of Research, fourth edition. Chicago: University of Chicago Press, 2016.

Collier, David; Fernando Daniel Hidalgo and Andra Olivia Maciuceanu, “Essentially contested concepts: debates and applications,” Journal of Political Ideologies, 11(3), October 2006, pp. 211–246.

Ekman, Paul. Telling Lies: Clues to Deceit in the Marketplace, Politics, and Marriage. New York: Norton, 1985.

Hilgartner, Stephen, “The Sokal affair in context,” Science, Technology, & Human Values, 22(4), Autumn 1997, pp. 506–522.

Lee, Bandy X. The Dangerous Case of Donald Trump: 27 Psychiatrists and Mental Health Experts Assess a President. New York: St. Martin’s Press, 2017.

Martin, Brian; and Florencia Peña Saint Martin. El mobbing en la esfera pública: el fenómeno y sus características [Public mobbing: a phenomenon and its features]. In Norma González González (Coordinadora), Organización social del trabajo en la posmodernidad: salud mental, ambientes laborales y vida cotidiana (Guadalajara, Jalisco, México: Prometeo Editores, 2014), pp. 91-114.

Martin, Brian. “Debating vaccination: understanding the attack on the Australian Vaccination Network.” Living Wisdom, no. 8, 2011, pp. 14–40.

Martin, Brian. “On the suppression of vaccination dissent.” Science & Engineering Ethics. Vol. 21, No. 1, 2015, pp. 143–157.

Martin, Brian. Evidence-based campaigning. Archives of Public Health, 76, no. 54. (2018), https://doi.org/10.1186/s13690-018-0302-4.

Martin, Brian. Vaccination Panic in Australia. Sparsnäs, Sweden: Irene Publishing, 2018.

Ken McLeod, “Meryl Dorey’s trouble with the truth, part 1: how Meryl Dorey lies, obfuscates, prevaricates, exaggerates, confabulates and confuses in promoting her anti-vaccination agenda,” 2010, http://www.scribd.com/doc/47704677/Meryl-Doreys-Trouble-With-the-Truth-Part-1.

Neuman, W. Lawrence. Social Research Methods: Qualitative and Quantitative Approaches, seventh edition. Boston, MA: Pearson, 2011.

Scott, Pam; Evelleen Richards and Brian Martin, “Captives of controversy: the myth of the neutral social researcher in contemporary scientific controversies,” Science, Technology, & Human Values, Vol. 15, No. 4, Fall 1990, pp. 474–494.

Sokal, Alan D. “What the Social Text affair does and does not prove,” in Noretta Koertge (ed.), A House Built on Sand: Exposing Postmodernist Myths about Science (New York: Oxford University Press, 1998), pp. 9–22

Stokes, Patrick. “No, you’re not entitled to your opinion,” The Conversation, 5 October 2012, https://theconversation.com/no-youre-not-entitled-to-your-opinion-9978.

Wright, Malcolm, and J. Scott Armstrong, “The ombudsman: verification of citations: fawlty towers of knowledge?” Interfaces, 38 (2), March-April 2008.

[1] Thanks to Meryl Dorey, Stephen Hilgartner, Larry Neuman, Alan Sokal and Malcolm Wright for valuable feedback on drafts.

[2] For informed commentary on these issues, see Bandy X. Lee, The Dangerous Case of Donald Trump: 27 Psychiatrists and Mental Health Experts Assess a President (New York: St. Martin’s Press, 2017).

[3] Pam Scott, Evelleen Richards and Brian Martin, “Captives of controversy: the myth of the neutral social researcher in contemporary scientific controversies,” Science, Technology, & Human Values, Vol. 15, No. 4, Fall 1990, pp. 474–494.

[4] The AVN, forced to change its name in 2014, became the Australian Vaccination-skeptics Network. In 2018 it voluntarily changed its name to the Australian Vaccination-risks Network.

[5] In 2014, SAVN changed its name to Stop the Australian (Anti-)Vaccination Network.

[6] Brian Martin and Florencia Peña Saint Martin. El mobbing en la esfera pública: el fenómeno y sus características [Public mobbing: a phenomenon and its features]. In Norma González González (Coordinadora), Organización social del trabajo en la posmodernidad: salud mental, ambientes laborales y vida cotidiana (Guadalajara, Jalisco, México: Prometeo Editores, 2014), pp. 91-114.

[7] Ken McLeod, “Meryl Dorey’s trouble with the truth, part 1: how Meryl Dorey lies, obfuscates, prevaricates, exaggerates, confabulates and confuses in promoting her anti-vaccination agenda,” 2010, http://www.scribd.com/doc/47704677/Meryl-Doreys-Trouble-With-the-Truth-Part-1.

[8] Brian Martin, “Debating vaccination: understanding the attack on the Australian Vaccination Network,” Living Wisdom, no. 8, 2011, pp. 14–40, at pp. 28–30.

[9] E.g., Paul Ekman, Telling Lies: Clues to Deceit in the Marketplace, Politics, and Marriage (New York: Norton, 1985).

[10] On Wikipedia I am categorised as an “anti-vaccination activist,” a term that is not defined on the entry listing those in the category. See Brian Martin, “Persistent bias on Wikipedia: methods and responses,” Social Science Computer Review, Vol. 36, No. 3, June 2018, pp. 379–388.

[11] See for example David Collier, Fernando Daniel Hidalgo and Andra Olivia Maciuceanu, “Essentially contested concepts: debates and applications,” Journal of Political Ideologies, 11(3), October 2006, pp. 211–246.

[12] Brian Martin. “Caught in the vaccination wars (part 3)”, 23 October 2012, http://www.bmartin.cc/pubs/12hpi-comments.html.

[13] The only possible exception to this statement is Michael Brull, “Anti-vaccination cranks versus academic freedom,” New Matilda, 7 February 2016, who reproduced my own summary of the key points in the thesis relevant to Australian government vaccination policy. For my responses to the attack, see http://www.bmartin.cc/pubs/controversy.html – Wilyman, for example “Defending university integrity,” International Journal for Educational Integrity, Vol. 13, No. 1, 2017, pp. 1–14.

[14] Brian Martin, Vaccination Panic in Australia (Sparsnäs, Sweden: Irene Publishing, 2018), pp. 15–24.

[15] E.g., Stuart Blume, Immunization: How Vaccines Became Controversial (London: Reaktion Books, 2017).

[16] Brian Martin. “Caught in the vaccination wars”, 28 April 2011, http://www.bmartin.cc/pubs/11savn/.

[17] For own commentary on Wakefield, see “On the suppression of vaccination dissent,” Science & Engineering Ethics, Vol. 21, No. 1, 2015, pp. 143–157.

[18] Brian Martin. Evidence-based campaigning. Archives of Public Health, Vol. 76, article 54, 2018, https://doi.org/10.1186/s13690-018-0302-4.

[19] Patrick Stokes, “No, you’re not entitled to your opinion,” The Conversation, 5 October 2012, https://theconversation.com/no-youre-not-entitled-to-your-opinion-9978.

[20] Martin, Vaccination Panic in Australia, 292–304.

[21] W. Lawrence Neuman, Social Research Methods: Qualitative and Quantitative Approaches, seventh edition (Boston, MA: Pearson, 2011), 3–5.

[22] Wayne C. Booth, Gregory G. Colomb, Joseph M. Williams, Joseph Bizup and William T. FitzGerald, The Craft of Research, fourth edition (Chicago: University of Chicago Press, 2016), 272–273.

[23] Malcolm Wright and J. Scott Armstrong, “The ombudsman: verification of citations: fawlty towers of knowledge?” Interfaces, 38 (2), March-April 2008, 125–132.

[24] For a detailed articulation of this approach, see Stephen Hilgartner, “The Sokal affair in context,” Science, Technology, & Human Values, 22(4), Autumn 1997, pp. 506–522. Hilgartner gives numerous citations to expansive interpretations of the significance of the hoax.

[25] See for example Alan D. Sokal, “What the Social Text affair does and does not prove,” in Noretta Koertge (ed.), A House Built on Sand: Exposing Postmodernist Myths about Science (New York: Oxford University Press, 1998), pp. 9–22, at p. 11: “From the mere fact of publication of my parody, I think that not much can be deduced. It doesn’t prove that the whole field of cultural studies, or the cultural studies of science — much less the sociology of science — is nonsense.”

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: Bernard Wills, Memorial University of Newfoundland and Labrador, bwills@grenfell.mun.ca.

Wills, Bernard. “On the Limits of Any Scientism.” Social Epistemology Review and Reply Collective 7, no. 7 (2018): 34-39.

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

See also:

Image by Vancouver Island University via Flickr / Creative Commons

 

Mizrahi is, alas, still confused though that perhaps is my fault. I did not attribute to him the view that non-scientific disciplines do not produce knowledge.[1] I am sorry if a cursory glance at my article created that impression but what I thought I had said was that this was the position known as strong scientism. Indeed, looking over my paper it seems that I made it quite clear that this position was ‘strong scientism’ and that Mizrahi defended something called ‘weak scientism’. According to this latter view the humane disciplines do indeed produce knowledge only of a qualitatively and quantitatively inferior kind. If this is not what weak scientism says I confess I don’t know what it says.

Thus, the opening salvo of his response, where he answers at some length a charge I did not make, has sailed clean over its intended target. (Mizrahi, 41-42) In my paper I distinguished weak scientism from strong scientism precisely on these grounds and then argued that the weaknesses of the former still dogged the latter: Mizrahi does not address this in his response. Here is a place where Mizrahi could have learned from humanities scholars and their practices of close reading and attended to the rhetorical and argumentative structure of my essay.

I began by critiquing ‘strong scientism’ which I said was not Mizrahi’s view and I did this by way of setting up my actual argument which was that Mizrahi’s proposed replacement ‘weak scientism’ suffered from the same basic flaws. I ask Mizrahi to read my response again and ask himself honestly if I accused him of being a proponent of ‘strong scientism’ rather than of ‘weak scientism’. To help him let me include the following citation from my piece:

I will focus, then, on the qualitative question and particularly on the claim that science produces knowledge and all the other things we tend to call knowledge are in fact not knowledge at all but something else. I will then consider Mr. Mizrahi’s peculiar version of this claim ‘weak scientism’ which is that while there may be knowledge of some sort outside of the sciences (it is hard, he thinks, to show otherwise) this knowledge is of a qualitatively lesser kind. (Wills, 18)

Asking Why Quantity of Production Matters

Mizrahi is still on about quantity. (Mizrahi, 42) I really have no idea why he is obsessed with this point. However, as he regards it as essential to ‘weak scientism’ I will quote what I said in a footnote to my essay: “Does Mizrahi mean to say that if a particular sub-discipline of English produces more articles in a given year than a small subfield of science then that discipline of English is superior to that subfield of science? I’m sure he does not mean to say this but it seems to follow from his words.” This point is surely not lost on him.

I have no firm opinion at all as to whether the totality of the sciences have produced more ‘stuff’ than the totality of the humanities between 1997 and 2017 and the reason is that I simply don’t care. I don’t accept quantity as a valid measure here unless it is backed up by qualitative considerations and if Mizrahi can’t make the case on qualitative grounds then quantity is simply irrelevant for the reason I gave: there are more commercials than there are artistic masterpieces. However, if Mizrahi still wants to fuss over quantitative metrics he faces the problem I raised.

While science in a global sense may indeed produce more sheer bulk of material than English, say, if there are subfields of science that do not produce more knowledge than subfields of English by this measure these must be inferior. Plus, what if it were true that Shakespeare scholars produced more papers than physicists? Would that cause Mizrahi to lower his estimate of physics? He would be an odd man if he did.

At any rate, there are all kinds of extrinsic reasons why scientific papers are so numerous that include the interests of corporations, governments, militaries and so on. The fact that there is so much science does not by itself indicate that there is anything intrinsically better about science and if science is intrinsically better that fact stands no matter how much of it there happens to be.

On the Power of Recursivity

To my argument that recursive processes can produce an infinite amount of knowledge he replies with an ineffectual jibe: “good luck publishing that!” (46) Well I am happy to inform him that I have indeed published ‘that’. I have published a number of papers on ancient and early modern philosophy that touch on the question of reflexivity and its attendant paradoxes as Mizrahi can find out by googling my name. Since he is so concerned about purely extrinsic measures of scholarly worth he will have to admit that there are in fact journals happy to ‘publish that’ and to that extent my point stands by his own chosen metric.

At any rate, in a further answer to this charge we get the following sophism: Besides, just as “recursive processes can extend our knowledge indefinitely in the field of mathematics,” they can also extend our knowledge in other fields as well, including scientific fields. That is, one “can produce a potential infinity of knowledge simply by reflecting recursively on the” (Wills 2018, 23) (sic) Standard Model in physics or any other scientific theory and/or finding. For this reason, Wills’ objection does nothing at all to undermine Weak Scientism.” (46)

Of course we can extend our knowledge indefinitely by reflecting on the standard model in physics just as Augustine says. But this has nothing whatsoever to do with whether a proposition is scientific or not. It can be done with any proposition at all. Nor is recursive doubling a scientific procedure in the terms described by Mizrahi. This is why quantitative claims about the superiority of science can never succeed unless, as I have said many times, they are backed up with qualitative considerations which would render a quantitative argument unnecessary.

On the Intentionality of the Ism

Mizrahi makes the standard response to the concerns I raised about sexism and colonialism. He denies he is a racist and indeed, Fox News style, turns the charge back on me. (44-45) He should understand, however, that my concern here is not personal but systemic racism. The version of scientific ideology he proposes has a history and that history is not innocent. It is a definition of knowledge and as such it has a social and political dimension. Part of this has been the exclusion of various others such as women or indigenous peoples from the socially sanctioned circle of knowers. This is the ‘privilege’ I refer to in my paper.

Mizrahi, as a participant in a certain tradition or practice of knowledge that claims and can often assert hegemony over other discourses, benefits from that privilege. That is not rocket science. Nor is the fact that, rightly or wrongly, Mizrahi is making hegemonic claims for science from which he himself stands to benefit. It is nothing to the point for Mizrahi to proclaim his innocence of any such intention or to use the ‘you are the real racist for calling me a racist’ ploy. As anyone familiar with the discourse about racism and colonialism can tell him, intention is not the salient feature of this sort of analysis but overall effect.

Also he has not distinguished an ideological critique from an ad hominem attack. I am not attacking him as a person but simply pointing that the position he takes on scientism has social, political and monetary implications that make his defense of weak-scientism ideologically loaded. And let me emphasize again that this has nothing whatsoever to do with Mizrahi’s intentions or personal feelings: I am happy to consider him a perfect gentleman. Perhaps a consideration of Marx would help him see this point a bit better and I can assure Mizrahi that Marx’s impact rating is stellar.

So Who Is Correct?

Of course, as Mizrahi says, all this is forgivable if his overall thesis is correct. (45) Apparently, I truly did not understand that “Even if it is true that “craft knowledge has roughly 3 million-year head start,” it is irrelevant to whether Weak Scientism is true or false. This is because Weak Scientism is a thesis about academic knowledge or research produced by academic fields of study (Mizrahi 2017a, 356; Mizrahi 2017b, 11; Mizrahi 2018a, 12). (46) I admit this point did escape me.[2]

This means that if I find knowledge produced outside the academy with qualities comparable to scientific knowledge that is irrelevant to the argument. Well, by all means then, let me limit my consideration to the academy since Mizrahi has defined that as his sole battleground. I gave many examples of knowledge in my paper that come from an academic context. Let us consider these with respect to Mizrahi’s chosen criteria for “good explanations, namely, unification, coherence, simplicity, and testability (Mizrahi 2017a, 360-362; Mizrahi 2017b, 19-20; Mizrahi 2018a, 17).” (47) (46)

Mizrahi seems to think this applies to a statement I made about Joyce scholars. (47) Let me take them as my ‘academic’ example. I take it as a given that a masterful exposition of Portrait of the Artist as Young Man will show the unity, coherence and simplicity of the work’s design to the extent that these are artistically desired features. What about testability? How does a Joyce scholar test what he says? As I said he tests it against the text. He does this in two ways.

First on the level of direct observation he establishes what Stephen Daedalus, say, does on page 46. This is, as far as I can see, a perfectly reputable kind of knowledge and if we can answer the question about page 46 directly we do not need to resort to any more complex explanatory processes. The fact that such a procedure is perfectly adequate to establish the truth means that scientific procedures of a more complex kind are unnecessary. The use of scientific method, while it may mean better knowledge in many cases, does not mean better knowledge here so Mizrahi’s complaint on this score is beside the point. (47)

Statue of James Joyce in Dublin, Ireland
Image by Loic Pinseel via Flickr / Creative Commons

What Can Improve Knowledge?

Of course, the Joyce scholar will also have an interpretation of Portrait of the Artist as a Young Man. This is where he answers broader questions about the work’s meaning, structure, unity and so on. This also entails the test of looking at the text not at any particular point but as a whole. What in this hermeneutic process would be improved by ‘scientific method’ as Mizrahi describes it? Where does the Joyce scholar need to draw testable consequences from a novel hypothesis and test it with an experiment? What would that even mean in this context?

His test is close reading as this is practiced in the discipline of English literature and he has peers who judge if he has done this well or badly. What is amiss with this process that it could be improved by procedures that have nothing to do with determining the meaning and significance of books? How on this question could science even begin to show its supposed ‘superiority’? It seems to me the only option for Mizrahi here is to deny that the Joyce scholar knows anything (beyond bare factual information) and this means, alas, that his position once again collapses into strong scientism.

I think, however, that I see where Mizrahi’s confusion lies. He seems to think I am saying the following: Joyce scholars look at a book to determine a fact just as scientists look at the world to determine a fact ergo Joyce scholars are scientists. (47) Let me reassure him I am not so jejune. Of course, field notes and other forms of direct observation are part of the arsenal of science. Plus, scientific statements are, at the end of the day, brought into relationship with observation either directly or indirectly. Still, Joyce scholars do not just look at page numbers or what characters are wearing in Chapter 2. They formulate interpretations of Joyce.

In this way too scientists not only observe things but formulate and test hypotheses, construct theories and so on. In some ways these may be comparable processes but they are not identical. Hermeneutics is not just an application of hyothetico-deductive method to a book. Conclusions about Joyce are not products of experimental testing and I can conceive of no way in which they could be strengthened by them except in a purely ancillary sense (ie. we might learn something indirect about Ulysses by exhuming Joyce’s bones).

Thus, Mizrahi’s argument that scientific explanations have more ‘good-making properties’ overall (47) is, whether true or not, irrelevant to the myriad of cases in which scientific explanations are either A. unnecessary or B. inapplicable. Once again we teeter on the brink of strong scientism (which Mizrahi rejects) for we are now forced to say that if a scientific explanation of a phenomenon is not to be had then there can be no other form of explanation.

There Are Radical Differences in How Knowledge Is Produced

Let me go back to my daughter who was not out in a field or cave somewhere but in a university classroom when she presented her analysis of Scriabin’s Prometheus chord. This, I hope, satisfies Mizrahi’s demand that I confine myself to an ‘academic’ context. Both her instructor and her classmates agreed that her analysis was sound. Why? Because it was the clearest, simplest explanation that answered the question of how Scriabin created this chord. It was an abduction that the community of knowers of which she was a part found adequate and that was the end of the story.

The reason, let me emphasize again since Mizrahi has such trouble with the point, is that this was all the question required. Kristin did not deduce a “…consequence that follows from a hypothesis plus auxiliary hypothesis” (47) to be made subject of a testable prediction. Why? Because that is not how knowledge is produced in her domain and such a procedure would add no value to her conclusion which concerned not facts about the natural world but Scriabin’s thought processes and aesthetic intentions.

Again it seems that either Mizrahi must concede this point OR adopt the strong scientist position that Kristin only seems to know something about Scriabin while actually there is nothing to be known about Scriabin outside the experimental sciences. So, to make his case he must still explain why science can produce better results in music theory, which IS an academic subject, than explanatory procedures currently used in that domain. Otherwise the superiority of science is only contextual which is a trivial thesis denied by no one.

Thus, Mizrahi is still bedeviled by the same problem. How is science supposed to show its superiority in domains where its explanatory procedures are simply not necessary and would add no value to existing explanations? I do not think Mizrahi has established the point that:”…if distinct fields of study have the same aim (i.e., to explain), then their products (i.e., explanations) can be evaluated with respect to similar criteria, such as unification, coherence, simplicity, and testability (Mizrahi 2017a, 360-362; Mizrahi 2017b, 19-20; Mizrahi 2018a, 17). Mizrahi says ‘similar’ but his argument actually depends on these criteria being ‘identical’ such that we can judge all explanations by one pre-set standard: in this case hypothetico-deductive method.

But this is nonsense. All disciplines use abduction, true, but they do not all arrive at the ‘best explanation’ by the same procedures. Their procedures are analogical not univocal. Failure to see this distinction seems to be at the root of Mizrahi’s errors. Differing explanatory processes can be compared but not identified as can be seen if we imagine a classicist taking his copy of the Iliad down to the chemistry lab to be analyzed for its meaning. The Chemistry lab here is the classicist’s brain! To use a less flippant example though there are sciences such as paleontology that make liberal use of narrative reconstruction (i.e. how those hominid bones got in that tiny cave) which is a form of abduction that does not correspond simply to the standard H/D model. Still, the story the paleontologist reconstructs, if it is a good one, has unity, simplicity and coherence regardless of the fact that it has not achieved this by a robotic application of H/D but rather by another, less formalized, form of inference.

Thus, I think Mizrahi’s reforming zeal (48) has got the better of him. He does not help his case by issuing the Borg-like boast that ‘resistance is futile’. If I recall my Trek lore correctly, the boast that ‘resistance is futile’ ended in ignominious defeat. One final point. One should never proofread one’s own papers, I did indeed misspell Mizrahi for which I heartily apologize.

Contact details: bwills@grenfell.mun.ca

References

Mizrahi, Moti. “Weak Scientism Defended Once More.” Social Epistemology Review and Reply Collective 7, no. 6 (2018): 41-50.

Wills, Bernard. “Why Mizrahi Needs to Replace Weak Scientism With an Even Weaker Scientism.” Social Epistemology Review and Reply Collective 7, no. 5 (2018): 18-24.

[1] Though, as I point out in my response (Wills, 22), he clearly vacillates on this point.

[2] It is an odd kind of scientism that holds science is superior within the academy while leaving open the question of whether non-scientific knowledge outside the academy may be superior to science. However, if that is Mizrahi’s position I will not quibble.

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: Henry Bauer, Virginia Tech, hhbauer@vt.edu

Bauer, Henry. 2013. “Reply to Krimsky.” Social Epistemology Review and Reply Collective 2 (4): 13-15.

The PDF of the article gives specific page numbers. Shortlink: http://wp.me/p1Bfg0-IZ

Please refer to:

Krimsky sees or interprets the evidence differently than I do. Science has always been conservative, he writes, implying that there’s nothing new to note about that. By contrast, I claim that intolerance of minority views has increased quite palpably, and that there are powerful institutional forces driving intolerance that were not earlier in play.

I’m a little puzzled that Krimsky didn’t recognize the strength of the evidence of change since his own book, Science in the Private Interest (2003; which I cite at a number of points), documents so well the degree to which late-20th-century science has been corrupted by personal and corporate conflicts of interest, which was not the case in earlier times. Continue Reading…