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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

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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: Nadja El Kassar, Swiss Federal Institute of Technology, nadja.elkassar@gess.ethz.ch

El Kassar, Nadja. “The Irreducibility of Ignorance: A Reply to Peels.” Social Epistemology Review and Reply Collective 8, no. 2 (2019): 31-38.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-46K

Image by dima barsky via Flickr / Creative Commons

 

This article responds to critiques of El Kassar, Nadja (2018). “What Ignorance Really Is: Examining the Foundations of Epistemology of Ignorance.” Social Epistemology. DOI: 10.1080/02691728.2018.1518498.

Including Peels, Rik. “Exploring the Boundaries of Ignorance: Its Nature and Accidental Features.” Social Epistemology Review and Reply Collective 8, no. 1 (2019): 10-18.

Thanks to Rik Peels for his thought-provoking comments which give me the opportunity to say more about the arguments and rationale of my article and the integrated conception. 

General Remarks About Two Approaches to Ignorance

Rik Peels’ and Patrick Bondy’s replies allow me to highlight and distinguish two approaches to ignorance, one that focuses on ignorance as a simple doxastic (propositional) phenomenon and another that regards ignorance as a complex epistemological phenomenon that is constituted by a doxastic component and by other epistemic components. The distinction can be illustrated by Peels’ conception and my integrated conception of ignorance proposed in the article. Peels’ conception belongs with the first approach, my conception belongs with the second approach.

As Peels’ reply also evinces, the two approaches come with different assumptions and consequences. For example, the first approach presupposes that accounts of knowledge and ignorance are symmetrical and/or mirror each other and, consequently, it will expect that an account of ignorance has the same features as an account of knowledge.

In contrast, the second approach takes ignorance to be a topic in its own right and therefore it is not concerned by criticism that points out that its account of ignorance makes claims that an account of knowledge does not make or does not fit with an account of knowledge in other ways. I will return to this distinction later. A major concern of the second approach (and my conception shares this concern) is to develop an account of ignorance sui generis, not an account of ignorance in the light of knowledge (or accounts of knowledge).

Why Peels’ Attempt at Reducing the Integrated Conception to His View Fails

Peels argues that the integrated conception of ignorance boils down to the conception of ignorance that he endorses. However, if I understand his considerations and arguments correctly, the observations can either be accommodated by my conception or my conception can give reasons for rejecting Peels’ assumptions. Let me discuss the three central steps in turn.

Doxastic Attitudes in the Second Conjunct

As a first step Peels notes that “the reference to doxastic attitudes in the second conjunct is … redundant” (Peels 2019, 11) since holding a false belief or holding no belief, the manifestations of ignorance, just are doxastic attitudes. But the doxastic attitudes in the second conjunct are not redundant because they capture second-order (and in general higher-order) attitudes towards ignorance, e.g. I am ignorant of the rules of Japanese grammar and I (truly) believe that I do not know these rules.

Socratic ignorance also includes more doxastic attitudes than those at the first level of ignorance. Those doxastic attitudes can also constitute ignorance. Peels’ observation indicates that it might be advisable for me to talk of meta-attitudes rather than doxastic attitudes to avoid confusion about the double appearance of doxastic attitudes.

Epistemic Virtues and Vices and the Nature of Ignorance

Peels’ second step concerns the other two components of the second conjunct. Epistemic virtues and vices “[do] not belong to the essence of being ignorant” (Peels 2019, 11). But I do not see what reasons Peels has for this claim. My arguments for saying that they do belong to the nature of being ignorant from the original article are still valid. One does not capture ignorance by focusing only on the doxastic component.

This is what my example of Kate and Hannah who are ignorant of the fact that cruise ships produce high emissions of carbon and sulfur dioxides but have different epistemic attitudes towards not knowing this fact and thus are ignorant in different ways is meant to show. Their being ignorant is not just determined by the doxastic component but also by their attitudes.

This does not mean that all ignorance comes with closed-mindedness or open-mindedness, it just means that all states of ignorance are constituted by a doxastic component and an attitudinal component (whichever attitudes fills that spot and whether it is implicit or explicit is an open question and depends on the relevant instance of ignorance). I am interested to hear which additional reasons Peels has for cutting epistemic virtues and vices from the second conjunct and delineating the nature of ignorance in the way that he does.

Ignorance as a Disposition?

Peels’ third step consists in a number of questions about ignorance as a disposition. He writes:

“[O]n the El Kassar synthesis, ignorance is a disposition that manifests itself in a number of dispositions (beliefs, lack of belief, virtues, vices). What sort of thing is ignorance if it is a disposition to manifest certain dispositions? It seems if one is disposed to manifest certain dispositions, one simply has those dispositions and will, therefore, manifest them in the relevant circumstances.” (Peels 2019, 12, emphasis in original).

These questions seem to indicate to Peels that the dispositional character of ignorance on the integrated conception is unclear and therefore disposition may be removed from the integrated conception. It does not make sense to say that ignorance is a disposition.

But Peels’ questions and conclusion themselves invite a number of questions and, therefore, I do not see how anything problematic follows for my conception. It is not clear to me whether Peels is worried because my conception implies that a disposition is manifested in another disposition that may be manifested or not, or whether he is concerned because my conception implies that one disposition (in the present context: ignorance) may have different stimulus conditions and different manifestations.

In reply to the first worry I can confirm that I think that it is possible that a disposition can be manifested in other dispositions. But I do not see why this is a problem. An example may help undergird my claim. Think e.g. of the disposition to act courageously, it is constituted at minimum by the disposition to take action when necessary and to feel as is appropriate. Aristotle’s description of the courageous person reveals how complicated the virtue is and that it consists in a number of dispositions:

Now the brave man is as dauntless as man may be. Therefore, while he will fear even the things that are not beyond human strength, he will fear them as he ought and as reason directs, and he will face them for the sake of what is noble; for this is the end of excellence. But it is possible to fear these more, or less, and again to fear things that are not terrible as if they were.

Of the faults that are committed one consists in fearing what one should not, another in fearing as we should not, another in fearing when we should not, and so on; and so too with respect to the things that inspire confidence. The man, then, who faces and who fears the right things and with the right aim, in the right way and at the right time, and who feels confidence under the corresponding conditions, is brave; for the brave man feels and acts according to the merits of the case and in whatever way reason directs. (Nicomachean Ethics, 1115b 17-22)

The fact that courage consists in other dispositions also explains why there are many ways to not be virtuously courageous. For the present context all that matters is that a disposition can consist in other dispositions that can be manifested or not.

The second worry might be alleviated by introducing the notion of multi-track dispositions into my argument. A multi-track disposition, a term widely acknowledged in philosophical work on disposition, is individuated by several pairs of stimulus conditions and manifestations (Vetter 2015, 34). Thus, ignorance as a disposition may be spelled out as a multi-track disposition that has different stimulus conditions and different manifestations.

Peels also argues against the view that epistemic virtues themselves are manifestations of ignorance. But I do not hold that epistemic virtues simpliciter are manifestations of ignorance, rather I submit that epistemic virtues (or vices) necessarily appear in manifestations of ignorance, they co-constitute ignorance.

Enveloped in Peels’ argument is another objection, namely, that epistemic virtues cannot appear in manifestations of ignorance, it is only epistemic vices that can be manifestations of ignorance – or as I would say: can appear in manifestations of ignorance. Peels claims that, “open-mindedness, thoroughness, and intellectual perseverance are clearly not manifestations of ignorance. If anything, they are the opposite: manifestations of knowledge, insight and understanding.” (Peels 2019, 12, emphasis in original)

Let me address this concern by explaining how ignorance can be related to epistemic virtues. Being open-mindedly ignorant, and being ignorant in an intellectually persevering way become more plausible forms and instantiations of ignorance if one recognizes the significance of ignorance in scientific research. Think, e.g., of a scientist who wants to find out how Earth was formed does not know how Earth was formed and she may dedicate her whole life to answering that question and will persist in the face of challenges and setbacks.

Similarly, for a scientist who wants to improve existing therapies for cancer and sets out to develop nanotechnological devices to support clinicians. She can be open-mindedly ignorant about the details of the new device. In fact, most scientists are probably open-mindedly ignorant; they do want to know more about what it is they do not know in their field and are after more evidence and insights. That is also one reason for conducting experiments etc. Firestein (2012) and several contributions in Gross and McGoey’s Routledge Handbook of Ignorance Studies (2015) discuss this connection in more detail.

Thus, Peels’ third step also does not succeed and as it stands the integrated conception thus does not reduce to Peels’ view. But I’d be interested to hear more about why such a revision of the integrated conception suggests itself.

Correction Concerning “How One Is Ignorant”

Let me address a cause of confusion in the integrated conception. When I call for an account of ignorance to explain “how one is ignorant”, I do not want the account to explain how one has become ignorant, i.e. provide a genetic or causal story of a particular state of ignorance. This assumption leads Peels and Bondy to their objections concerning causal components in my conception of the nature of ignorance.

Instead, what I require, is for an account of ignorance to capture what one’s ignorance is like, what epistemic attitudes the subject has towards the doxastic component of her ignorance. The confusion and the fundamental objections to the integrated conception may be explained by the different approaches of ignorance that I have mentioned at the start of my reply.

No Mirroring Nor Symmetry Required

Peels notes that theories of knowledge do not include a causal story of how the subject became knowledgeable, nor about the quality of the subject’s knowledge, and from this he concludes that the integrated conception of ignorance which he takes to provide such a causal story must be rejected. However, as it stands, his argument is not conclusive.

First, it builds on confusion about the claims of the integrated conception that I have addressed in the previous section (3): the integrated conception does not provide a causal story for how the subject became ignorant, nor does it claim that such a causal story should be part of an account of the nature of ignorance. Rather, it spells out which additional features of ignorance are also constitutive – namely, an epistemic attitude – in addition to the doxastic component accepted by everyone.

Second, it is unclear why theories of knowledge and theories of ignorance have to presuppose a current-time slice approach, as effectively endorsed by Peels. Some theories of knowledge want to distinguish lucky true belief from knowledge and therefore look at the causal history of the subject coming to their true belief and therefore reject current-time slice approaches (e.g. Goldman 2012).

Third, Peels’ objection presupposes that theories of knowledge and theories of ignorance have to contain the same constituents and features or have to be symmetrical or have to mirror each other in some way, but I do not see why these presuppositions hold. Knowledge and ignorance are obviously intimately connected but I am curious to hear further arguments for why their accounts have to be unified or symmetrical or mirrored.

The Distinction Between Necessary and Contingent or Accidental Features of Ignorance

Peels argues that my conception confuses necessary and contingent or accidental features of ignorance but it is not clear what reasons Peels can give to support his diagnosis. My conception specifically distinguishes necessary components of ignorance and contingent/accidental instantiations of a necessary component of ignorance.

Peels’ discussion of my example of Kate and Hannah who both do not know that cruise ships have bad effects for the environment seems to jumble necessary features of ignorance whose instantiation is contingent (e.g. open-mindedness instantiates the epistemic attitude-component in open-minded ignorance) and contingent features of ignorance that trace back the causal history of an instance of ignorance. Peels writes:

Hannah is deeply and willingly ignorant about the high emissions of both carbon and sulfur dioxides of cruise ships (I recently found out that a single cruise trip has roughly the same amount of emission as seven million cars in an average year combined). Kate is much more open-minded, but has simply never considered the issue in any detail. She is in a state of suspending ignorance regarding the emission of cruise ships.

I reply that they are both ignorant, at least propositionally ignorant, but that their ignorance has different, contingent features: Hannah’s ignorance is deep ignorance, Kate’s ignorance is suspending ignorance, Hannah’s ignorance is willing or intentional, Kate’s ignorance is not. These are among the contingent features of ignorance; both are ignorant and, therefore, meet the criteria that I laid out for the nature of ignorance. (Peels 2019, 16-17)

Hannah’s and Kate’s particular epistemic attitudes are (to some extent) contingent but the fact that ignorance consists in a doxastic component and an attitudinal component is not contingent but necessary. In other words: which epistemic attitude is instantiated is accidental, but that there is an epistemic attitude present is not accidental but necessary. That is what the integrated conception holds. I’m interested to hear more about Peels’ argument for the opposing claim in the light of these clarifications.

Being Constitutive and Being Causal

Peels’ argumentation seems to presuppose that something that is constitutive of a state or disposition cannot also be causal, but it is not clear why that should be the case. E.g. Elzinga (2018) argues that epistemic self-confidence is constitutive of intellectual autonomy and at the same time may causally contribute to intellectual autonomy.

And note also that a constitutive relation between dispositions does not have to entail a causal relation in the sense of an efficient cause. Some authors in Action Theory argue that a disposition is not the cause of an action; rather, a decision, motivation, desire (etc.) is the cause of the action (cf. Löwenstein 2017, 85-86). I do not want to take sides on this issue, this is just to point out that Peels’ approach to something being constitutive and being a cause is not straightforward. (See also Section 4 in my upcoming reply to Patrick Bondy.)

Other Forms of Ignorance

Peels notes that my approach does not capture objectual and procedural ignorance as spelled out by Nottelmann (e.g. Nottelmann 2016). He tries to show that the integrated conception does not work for lack of know-how: “not knowing how to ride a bike does not seem to come with certain intellectual virtues or vices” (Peels 2019, 13) nor for lack of objectual ignorance: “if I am not familiar with the smell of fresh raspberries, that does not imply any false beliefs or absence of beliefs, nor does it come with intellectual virtues or vices” (Peels 2019, 13).

I am glad that Peels picks out this gap in the article, as does Bondy. It is an important and stimulating open question how the integrated conception fits with such other forms of ignorance – I am open-mindedly ignorant with respect to its answers. But the article did not set out to give an all-encompassing account of ignorance. Nor is it clear, whether one account will work for all forms of ignorance (viz. propositional ignorance, objectual ignorance, technical/procedural ignorance). Peels’ observation thus highlights an important open question for all theories of ignorance but not a particular objection against my integrated conception.

At the same time, I am skeptical whether Peels’ proposed account, the threefold synthesis, succeeds at capturing objectual and procedural ignorance. I do not see how the threefold synthesis is informative regarding objectual and procedural ignorance since it just states that objectual ignorance is “lack of objectual knowledge” and procedural ignorance is “lack of procedural knowledge”. Peels’ formulates the Threefold Synthesis as follows, with an additional footnote:

Threefold Synthesis: Ignorance is an epistemic agent’s lack of propositional knowledge or lack of true belief, lack of objectual knowledge, or lack of procedural knowledge.9

9If the Standard View on Ignorance is correct, then one could simply replace this with: Ignorance is a disposition of an epistemic agent that manifests itself in lack of (propositional, objectual, or procedural) knowledge. (Peels 2019, 13)

I do not see how these statements go toward capturing lack of competence, e.g. not possessing the competence to ski, or lack of objectual knowledge, e.g. not knowing Paris. I guess that philosophers interested in ignorance and in this issue will have to carefully study the phenomena that they want to capture and their interrelations – as Bondy starts to do in his Reply (Bondy 2018, 12-14) – in order to set out to adequately capture what Peels calls lack of objectual knowledge or lack of procedural knowledge.

What Does One Want From an Account of Ignorance?

Peels’ reply evinces that anyone who wants to develop an account of ignorance needs to answer a number of fundamental questions, including: What is it that we want from an account of ignorance? Do we want it a unified account for knowledge and ignorance? Do we want a simple account? Or do we want to adequately capture the phenomenon and be able to explain its significance in epistemic practices of epistemic agents? I want the account to be able to do the latter and have therefore put forward the integrated conception.

Two Clarificatory Remarks

In closing, I would like to add two clarificatory remarks. Peels suggests that the structural conception and agnotology are identical conceptions or approaches (Peels 2019, 15-16). But even though there are signficant connections between the structural conception and agnotology, they are distinct.

The examples for the structural conception in my article are from feminist epistemology of ignorance, not from agnotology. I do not want to engage in labelling and including or excluding authors and their works from fields and disciplines, but there are differences between works in epistemology of ignorance and agnotology since agnotology is often taken to belong with history of science. I would not want to simply identify them.

I do not see how Peels’ observations that the examples for agential conceptions of ignorance include causal language and that the conception of ignorance that he finds in critical race theory does not fit with someone being ignorant “of the fact that Antarctica is the largest desert on earth” (Peels 2019, 14) present objections to the integrated conception.

If there are claims about the causes of ignorance in these theories, that does not mean that my conception, which is distinct from these conceptions, makes the same claims. I specifically develop a new conception because of the advantages and disadvantages of the different conceptions that I discuss in the article.[1]

Contact details: nadja.elkassar@gess.ethz.ch

References

Aristoteles. 1995. The Complete Works of Aristotle: The Revised Oxford Translation. Volume Two. Edited by Jonathan Barnes. Princeton, NJ: Princeton Univ. Press.

Bondy, Patrick. 2018. “Knowledge and Ignorance, Theoretical and Practical.” Social Epistemology Review and Reply Collective 7 (12): 9–14.

Elzinga, Benjamin. 2019. “A Relational Account of Intellectual Autonomy.” Canadian Journal of Philosophy 49 (1): 22–47. https://doi.org/10.1080/00455091.2018.1533369.

Firestein, Stuart. 2012. Ignorance: How It Drives Science. Oxford, New York: Oxford University Press.

Goldman, Alvin I. 2012. Reliabilism and Contemporary Epistemology: Essays. New York, NY.: Oxford Univ. Press.

Gross, Matthias, and Linsey McGoey, eds. 2015. Routledge International Handbook of Ignorance Studies. Routledge International Handbooks. London ; New York: Routledge, Taylor & Francis Group.

Löwenstein, David. 2017. Know-How as Competence: A Rylean Responsibilist Account. Studies in Theoretical Philosophy, vol. 4. Frankfurt am Main: Vittorio Klostermann.

Nottelmann, Nikolaj. 2016. “The Varieties of Ignorance.” In The Epistemic Dimensions of Ignorance, edited by Rik Peels and Martijn Blaauw, 33–56. Cambridge: Cambridge University Press. https://doi.org/10.1017/9780511820076.003.

Peels, Rik. 2019. “Exploring the Boundaries of Ignorance: Its Nature and Accidental Features.” Social Epistemology Review and Reply Collective 8 (1): 10–18.

Vetter, Barbara. 2015. Potentiality: From Dispositions to Modality. Oxford: Oxford University Press.

[1] Thanks to David Löwenstein and Lutz Wingert for helpful discussions.

Author Information: Fabien Medvecky, University of Otago, fabien.medvecky@otago.ac.nz.

Medvecky, Fabien. “Institutionalised Science Communication and Epistemic Injustice.” Social Epistemology Review and Reply Collective 8, no. 2 (2019): 15-20.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-46m

A graffiti mural that was, and may even still be, on Maybachufer Strasse in Kreuzberg, Berlin.
Image by Igal Malis via Flicker / Creative Commons

 

This article responds to Matheson, Jonathan, and Valerie Joly Chock. “Science Communication and Epistemic Injustice.” Social Epistemology Review and Reply Collective 8, no. 1 (2019): 1-9.

In a recent paper, I argued that science communication, the “umbrella term for the research into and the practice of increasing public understanding of and public engagement with science”, is epistemically unjust (Medvecky, 2017). Matheson and Chock disagree. Or at least, they disagree with enough of the argument to conclude that “while thought provoking and bold, Medvecky’s argument should be resisted” (Matheson & Chock, 2019). This has provided me with an opportunity to revisit some of my claims, and more importantly, to make explicit those claims that I had failed to make clear and present in the original paper. That’s what this note will do.

Matheson and Chock’s concern with the original argument is two-fold. Firstly, they argue that the original argument sinned by overreaching, and secondly, that while there might be credibility excess, such excess should not be viewed as constituting injustice. I’ll begin by outlining my original argument before tackling each of their complaints.

The Original Argument For the Epistemic Injustice of Science Communication

Taking Matheson and Chock’s formal presentation of the original argument, it runs as follows:

1. Science is not a unique and privileged field (this isn’t quite right. See below for clarification)

2. If (1), then science communication creates a credibility excess for science.

3. Science communication creates a credibility excess for science.

4. If (3), then science communication is epistemically unjust.

5. Science communication is epistemically unjust.

The original argument claimed that science was privileged in the way that its communication is institutionalised through policy and practices in a way not granted to other fields, and that fundamentally,

While there are many well-argued reasons for communicating, popularizing, and engaging with science, these are not necessarily reasons for communicating, popularizing, and engaging only with science. Focusing and funding only the communication of science as reliable knowledge represents science as a unique and privileged field; as the only reliable field whose knowledge requires such specialized treatment. This uniqueness creates a credibility excess for science as a field. (italic added)

Two clarificatory points are important here. Firstly, while Matheson and Chock run with premise 1, they do express some reservation. And so would I if this were the way I’d spelled it out. But I never suggested that there is nothing unique about science. There undoubtedly is, usually expressed in terms of producing especially reliable knowledge (Nowotny, 2003; Rudolph, 2014).

My original argument was that this isn’t necessarily enough to warrant special treatment when it comes to communication. As I stated then, “What we need is a reason for why reliable knowledge ought to be communicated. Why would some highly reliable information about the reproductive habits of a squid be more important to communicate to the public than (possibly less reliable) information about the structure of interest rates or the cultural habits of Sufis?” (Italic added)

In the original paper, I explicitly claimed, “We might be able to show that science is unique, but that uniqueness does not relate to communicative needs. Conversely, we can provide reasons for communicating science, but these are not unique to science.” (Medvecky, 2017)

Secondly, as noted by Matheson and Chock, the concern in the original argument revolves around “institutionalized science communication; institutionalized in government policies on the public understanding of and public engagement with the sciences; in the growing numbers of academic journals and departments committed to further the enterprise through research and teaching; in requirements set by funding bodies; and in the growing numbers of associations clustering under the umbrella of science communication across the globe.”

What maybe wasn’t made explicit was the role and importance of this institutionalization which is directed by government strategies and associated funding policies. Such policies are designed specifically and uniquely to increase public communication of and public engagement with science (MBIE, 2014).

They may mention that science should be read broadly, such as the UK’s A vision for Science and Society (DIUS, 2008) which states “By science we mean all-encompassing knowledge based on scholarship and research undertaken in the physical, biological, engineering, medical, natural and social disciplines, including the arts and humanities”. Yet the policy also claims that “These activities will deliver a coherent approach to increasing STEM skills, with a focus on improved understanding of the link between labour market needs and business demands for STEM skills and the ability of the education system to deliver flexibly into the 21st century.”

STEM (science, technology, engineering and mathematics) is explicitly not a broad view of science; it’s specifically restricted to the bio-physical science and associated fields. If science was truly meant broadly, there’d be no need to specify STEM. These policies, including their funding and support, are uniquely aimed at science as found in STEM, and it is this form of institutionalized and institutionally sponsored science communication that is the target of my argument.

With these two points in mind, let me turn to Matheson and Chock’s objections.

The Problem of Overreaching and the Marketplace of Ideas

Matheson and Chock rightly spell out my view when stating that the “fundamental concern is that science communication represents scientific questions and knowledge as more valuable than questions and knowledge in other domains.” What they mistake is what I take issue with. Matheson and Chock claim, “When it comes to scientific matters, we should trust the scientists more. So, the claim cannot be that non-scientists should be afforded the same amount of credibility on scientific matters as scientists”. Of course, who wouldn’t agree with that!

For Matheson and Chock, given their assumption that science communication is equivalent to scientists communicating their science, it follows that it is only reasonable to give special attention to the subject or field one is involved in. As they say,

Suppose that a bakery only sells and distributes baked goods. If there is nothing unique and privileged about baked goods – if there are other equally important goods out there (the parallel of premise (1)) – then Medvecky’s reasoning would have it that the bakery is guilty of a kind of injustice by virtue of not being in the business of distributing those other (equally valuable) goods.

But they’re mistakenly equating science communication with communication by scientists about their science. This suggests both a misunderstanding of my argument and a skewed view of what science communication is.

To tackle the latter first, while some science communication efforts come from scientists, science communication is much broader. Science communication is equally carried out by (non-scientist) journalists, (non-scientist) PR and communication officers, (non-scientist) policy makers, etc. Indeed, some of the most popular science communicators aren’t scientists at all, such as Bill Bryson. So the concern is not with the bakery privileging baked goods, it’s with baked goods being privileged simpliciter.

As discussed in both my original argument and in Matheson and Chock’s reply, my concern revolves around science communication institutionalized through policies and such like. And that’s where the issue is; there is institutionalised science communication, including policy with significant funding such that there can be specific communication, and that such policies exist only for the sciences. Indeed, there are no “humanities communications” governmental policies or funding strategies, for example. Science communication, unlike Matheson and Chock’s idealised bakery, doesn’t operate in anything like a free market.

Let’s take the bakery analogy and its position it in a marketplace a little further (indeed, thinking of science communication and where it sits in the market place of knowledge fits well). My argument is not that a bakery is being unjust by selling only baked goods.

My argument is that if bakeries were the only stores to receive government subsidies and tax breaks, and were, through governments and institutional intervention, granted a significantly better position in the street, then yes, this is unfair. Other goods will fail to have the same level of traction as baked goods and would be unable to compete on a just footing. This is not to say that the bakeries need to sell other goods, but rather, by benefiting from the unique subsidies, baked goods gain a marketplace advantage over goods in other domains, in the same way that scientific knowledge benefits from a credibility excess (ie epistemic marketplace advantage) over knowledge in other domains.

Credibility Excess and Systemic Injustices

The second main objection raised by Matheson and Chock turns on whether any credibility excess science might acquire in this way should be considered an injustice. They rightly point out that “mere epistemic errors in credibility assessments, however, do not create epistemic injustice. While a credibility excess may result in an epistemic harm, whether this is a case of epistemic injustice depends upon the reason why that credibility excess is given.”

Specifically, Matheson and Chock argue that for credibility excess to lead to injustice, this must be systemic and carry across contexts. And according to them, science communication is guilty of no such trespass (or, at the very least, my original argument fails to make the case for such).

Again, I think this comes down to how science communication is viewed. Thinking of science communication in institutionalised ways, as I intended, is indeed systemic. What Matheson and Chock have made clear is that in my original argument, I didn’t articulate clearly enough just how deeply the institutionalisation of science communication is, and how fundamentally linked with assumptions of the epistemic dominance of science this institutionalisation is. I’ll take this opportunity to provide some example of this.

Most obviously, there are nationally funded policies that aim “to develop a culture where the sciences are recognised as relevant to everyday life and where the government, business, and academic and public institutions work together with the sciences to provide a coherent approach to communicating science and its benefits”; policies backed by multi-million dollar investments from governments (DIISRTE, 2009).

Importantly, there are no equivalent for other fields. Yes, there are funds for other fields (funds for research, funds for art, etc), but not funds specifically for communicating these or disseminating their findings. And, there are other markers of the systemic advantages science holds over other fields.

On a very practical, pecuniary level, funding for research is rarely on a playing field. In New Zealand, for example, the government’s Research Degree Completion Funding allocates funds to departments upon students’ successfully completing their thesis. This scheme grants twice as much to the sciences as it does to the social sciences, humanities, and law (Commission, 2016).

In practice, this means a biology department supervising a PhD thesis on citizen science in conservation would, on thesis completion, receive twice the fund that a sociology department supervising the very same thesis would receive. And this simply because one field delivers knowledge under the tag of science, while the other under the banner of the humanities.

At a political level the dominance of scientific knowledge is also evident. While most countries have a Science Advisor to the President or Chief Science Advisor to the Prime Minister, there are no equivalent “Chief Humanities Advisor”. And the list of discrepancies goes on, with institutionalised science communication a key player. Of course, for each of these examples of where science and scientific knowledge benefits over other fields, some argument could be made for why this or that case does indeed require that science be treated differently.

But this is exactly why the credibility excess science benefits from is epistemically unjust; because it’s not simply ‘a case here to be explained’ and ‘a case there to be explained’. It’s systemic and carries across context. And science communication, by being the only institutionalised communication of a specific knowledge field, maintains, amplifies, and reinforces this epistemic injustice.

Conclusion

When I argued that science communication was epistemically unjust, my claim was directed at institutionalised science communication, with all its trimmings. I’m grateful to Matheson and Chock for inviting to re-read my original paper and see where I may have failed to be clear, and to think more deeply about what motivated my thinking.

I want to close on one last point Matheson and Chock brought up. They claimed that it would be unreasonable to expect science communicators to communicate other fields. This was partially in response to my original paper where I did suggest that we should move beyond science communication to something like ‘knowledge communication’ (though I’m not sure exactly what that term should be, and I’m not convince ‘knowledge communication’ is ideal either).

Here, I agree with Matheson and Chock that it would be silly to expect those with expertise in science to be obliged to communicate more broadly about fields beyond their expertise (though some of them do). The obvious answer might be to have multiple branches of communication institutionalised and equally supported by government funding, by advisors, etc: science communication; humanities communication; arts communication; etc. And I did consider this in the original paper.

But the stumbling block is scarce resources, both financially and epistemically. Financially, there is a limit to how much governments would be willing to fund for such activates, so having multiple branches of communication would become a deeply political ‘pot-splitting’ issue, and there, the level of injustice might be even more explicit. Epistemically, there is only so much knowledge that we, humans, can process. Simply multiplying the communication of knowledge for the sake of justice (or whatever it is that ‘science communication’ aims to communicate) may not, in the end, be particularly useful without some concerted and coordinate view as to what the purpose of all this communication was.

In light of this, there is an important question for us in social epistemology: as a society funding and participating in knowledge-distribution, which knowledge should we focus our ‘public-making’ and communication efforts on, and why? Institutionalised science communication initiatives assume that scientific knowledge should hold a special, privileged place in public communication. Perhaps this is right, but not simply on the grounds that “science is more reliable”. There needs to be a better reason. Without one, it’s simply unjust.

Contact details: fabien.medvecky@otago.ac.nz

References

Commission, T. T. E. (2016). Performance-Based Research Fund (PBRF) User Manual. Wellington, New Zealand: Tertiary Education Commission.

DIISRTE. (2009). Inspiring Australia: A national strategy for engagement with the sciences.  Canberra: Commonwealth of Australia.

DIUS. (2008). A vision for Science and Society: A consultation on developing a new strategy for the UK: Department for Innovation, Universities, and Skills London.

Matheson, J., & Chock, V. J. (2019). Science Communication and Epistemic Injustice. SERRC, 8(1).

MBIE. (2014). A Nation of Curious Minds: A national strategic plan for science in society.  Wellington: New Zealand Government.

Medvecky, F. (2017). Fairness in Knowing: Science Communication and Epistemic Justice. Science and engineering ethics. doi: 10.1007/s11948-017-9977-0

Nowotny, H. (2003). Democratising expertise and socially robust knowledge. Science and Public Policy, 30(3), 151-156. doi: 10.3152/147154303781780461

Rudolph, J. L. (2014). Why Understanding Science Matters:The IES Research Guidelines as a Case in Point. Educational Researcher, 43(1), 15-18. doi: 10.3102/0013189×13520292

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

Kochan, Jeff. “Suppressed Subjectivity and Truncated Tradition: A Reply to Pablo Schyfter.” Social Epistemology Review and Reply Collective 7, no. 12 (2018): 15-21.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-44s

Image by Brandon Warren via Flickr / Creative Commons

 

This article responds to: Schyfter, Pablo. “Inaccurate Ambitions and Missing Methodologies: Thoughts on Jeff Kochan and the Sociology of Scientific Knowledge.” Social Epistemology Review and Reply Collective 7, no. 8 (2018): 8-14.

In his review of my book – Science as Social Existence: Heidegger and the Sociology of Scientific Knowledge – Raphael Sassower objects that I do not address issues of market capitalism, democracy, and the ‘industrial-academic-military complex’ (Sassower 2018, 31). To this, I responded: ‘These are not what my book is about’ (Kochan 2018, 40).

In a more recent review, Pablo Schyfter tries to turn this response around, and use it against me. Turnabout is fair play, I agree. Rebuffing my friendly, constructive criticism of the Edinburgh School’s celebrated and also often maligned ‘Strong Programme’ in the Sociology of Scientific Knowledge (SSK), Schyfter argues that I have failed to address what the Edinburgh School is actually about (Schyfter 2018, 9).

Suppressing the Subject

More specifically, Schyfter argues that I expect things from the Edinburgh School that they never intended to provide. For example, he takes what I call the ‘glass bulb’ model of subjectivity, characterises it as a ‘form of realism,’ and then argues that I have, in criticising the School’s lingering adherence to this model, failed to address their ‘actual intents’ (Schyfter 2018, 8, 9). According to Schyfter, the Edinburgh School did not have among its intentions the sorts of things I represent in the glass-bulb model – these are not, he says, what the School is about.

This claim is clear enough. Yet, at the end of his review, Schyfter then muddies the waters. Rather than rejecting the efficacy of the glass-bulb model, as he had earlier, he now tries ‘expanding’ on it, suggesting that the Strong Programme is better seen as a ‘working light bulb’: ‘It may employ a glass-bulb, but cannot be reduced to it’ (Schyfter 2018, 14).

So is the glass-bulb model a legitimate resource for understanding the Edinburgh School, or is it not? Schyfter’s confused analysis leaves things uncertain. In any case, I agree with him that the Edinburgh School’s complete range of concerns cannot be reduced to those specific concerns I try to capture in the glass-bulb model.

The glass-bulb model is a model of subjectivity, and subjectivity is a central topic of Science as Social Existence. It is remarkable, then, that the word ‘subject’ and its cognates never appear in Schyfter’s review (apart from in one quote from me). One may furthermore wonder why Schyfter characterises the glass-bulb model as a ‘form of realism.’ No doubt, these two topics – subjectivity and realism – are importantly connected, but they are not the same. Schyfter has mixed them up, and, in doing so, he has suppressed subjectivity as a topic of discussion.

Different Kinds of Realism

Schyfter argues that I am ‘unfair’ in criticising the Edinburgh School for failing to properly address the issue of realism, because, he claims, ‘[t]heir work was not about ontology’ (Schyfter 2018, 9). As evidence for my unfairness, he quotes my reference to ‘the problem of how one can know that the external world exists’ (Schyfter 2018, 9; cf. Kochan 2017, 37). But the problem of how we can know something is not an ontological problem, it is an epistemological one, a problem of knowledge. Schyfter has mixed things up again.

Two paragraphs later, Schyfter then admits that the Edinburgh School ‘did not entirely ignore ontology’ (Schyfter 2018, 9). I agree. In fact, as I demonstrate in Chapter One, the Edinburgh School was keen to ontologically ground the belief that the ‘external world’ exists. Why? Because they see this as a fundamental premise of science, including their own social science.

I criticise this commitment to external-world realism, because it generates the epistemological problem of how one can know that the external world exists. And this epistemological problem, in turn, is vulnerable to sceptical attack. If the world is ‘external,’ the question will arise: external to what? The answer is: to the subject who seeks to know it.

The glass-bulb model reflects this ontological schema. The subject is sealed inside the bulb; the world is external to the bulb. The epistemological problem then arises of how the subject penetrates the glass barrier, makes contact with – knows – the world. This problem is invariably vulnerable to sceptical attack. One can avoid the problem, and the attack, by fully jettisoning the glass-bulb model. Crucially, this is not a rejection of realism per se, but only of a particular form of realism, namely, external-world realism.

Schyfter argues that the Edinburgh School accepts a basic premise, ‘held implicitly by people as they live their lives, that the world with which they interact exists’ (Schyfter 2018, 9). I agree; I accept it too. Yet he continues: ‘Kochan chastises this form of realism because it does not “establish the existence of the external world”’ (Schyfter 2018, 9).

That is not quite right. I agree that people, as they live their lives, accept that the world exists. But this is not external-world realism, and it is the latter view that I oppose. I ‘chastise’ the Edinburgh School for attempting to defend the latter view, when all they need to defend is the former. The everyday realist belief that the world exists is not vulnerable to sceptical attack, because it does not presuppose the glass-bulb model of subjectivity.

On this point, then, my criticism of the Edinburgh School is both friendly and constructive. It assuages their worries about sceptical attack – which I carefully document in Chapter One – without requiring them to give up their realism. But the transaction entails that they abandon their lingering commitment to the glass-bulb model, including their belief in an ‘external’ world, and instead adopt a phenomenological model of the subject as being-in-the-world.

Failed Diversionary Tactics

It is important to note that the Edinburgh School does not reject scepticism outright. As long as the sceptic attacks absolutist knowledge of the external world, they are happy to go along. But once the sceptic argues that knowledge of the external world, as such, is impossible, they demur, for this threatens their realism. Instead, they combine realism with relativism. Yet, as I argue, as long as they also combine their relativism with the glass-bulb model, that is, as long as theirs is an external-world realism, they will remain vulnerable to sceptical attack.

Hence, I wrote that, in the context of their response to the external-world sceptic, the Edinburgh School’s distinction between absolute and relative knowledge ‘is somewhat beside the point’ (Kochan 2017, 48). In response, Schyfter criticises me for neglecting the importance of the Edinburgh School’s relativism (Schyfter 2018, 10). But I have done no such thing. In fact, I wholly endorse their relativism. I do suggest, however, that it be completely divorced from the troublesome vestiges of the glass-bulb model of subjectivity.

Schyfter uses the same tactic in response to this further claim of mine: ‘For the purposes of the present analysis, whether [conceptual] content is best explained in collectivist or individualist terms is beside the point’ (Kochan 2017, 79). For this, I am accused of failing to recognise the importance of the Edinburgh School’s commitment to a collectivist or social conception of knowledge (Schyfter 2018, 11).

The reader should not be deceived into thinking that the phrase ‘the present analysis’ refers to the book as a whole. In fact, it refers to that particular passage of Science as Social Existence wherein I discuss David Bloor’s claim that the subject can make ‘genuine reference to an external reality’ (Kochan 2017, 79; cf. Bloor 2001, 149). Bloor’s statement relies on the glass-bulb model. Whether the subjectivity in the bulb is construed in individualist terms or in collectivist terms, the troubles caused by the model will remain.

Hence, I cannot reasonably be charged with ignoring the importance of social knowledge for the Edinburgh School. Indeed, the previous but one sentence to the sentence on which Schyfter rests his case reads: ‘This sociological theory of the normativity and objectivity of conceptual content is a central pillar of SSK’ (Kochan 2017, 79). It is a central pillar of Science as Social Existence as well.

Existential Grounds for Scientific Experience

Let me shift now to Heidegger. Like previous critics of Heidegger, Schyfter is unhappy with Heidegger’s concept of the ‘mathematical projection of nature.’ Although I offer an extended defense and development of this concept, Schyfter nevertheless insists that it does ‘not offer a clear explanation of what occurs in the lived world of scientific work’ (Schyfter 2018, 11).

For Heidegger, ‘projection’ structures the subject’s understanding at an existential level. It thus serves as a condition of possibility for both practical and theoretical experience. Within the scope of this projection, practical understanding may ‘change over’ to theoretical understanding. This change-over in experience occurs when a subject holds back from immersed, practical involvement with things, and instead comes to experience those things at a distance, as observed objects to which propositional statements may then be referred.

The kind of existential projection specific to modern science, Heidegger called ‘mathematical.’ Within this mathematical projection, scientific understanding may likewise change over from practical immersion in a work-world (e.g., at a lab bench) to a theoretical, propositionally structured conception of that same world (e.g., in a lab report).

What critics like Schyfter fail to recognise is that the mathematical projection explicitly envelopes ‘the lived world of scientific work’ and tries to explain it (necessarily but not sufficiently) in terms of the existential conditions structuring that experience. This is different from – but compatible with – an ethnographic description of scientific life, which need not attend to the subjective structures that enable that life.

When such inattention is elevated to a methodological virtue, however, scientific subjectivity will be excluded from analysis. As we will see in a moment, this exclusion is manifest, on the sociology side, in the rejection of the Edinburgh School’s core principle of underdetermination.

In the mid-1930s, Heidegger expanded on his existential conception of science, introducing the term mathēsis in a discussion of the Scientific Revolution. Mathēsis has two features: metaphysical projection; and work experiences. These are reciprocally related, always occurring together in scientific activity. I view this as a reciprocal relation between the empirical and the metaphysical, between the practical and the theoretical, a reciprocal relation enabled, in necessary part, by the existential conditions of scientific subjectivity.

Schyfter criticises my claim that, for Heidegger, the Scientific Revolution was not about a sudden interest in facts, measurement, or experiment, where no such interest had previously existed. For him, this is ‘excessively broad,’ ‘does not reflect the workings of scientific practice,’ and is ‘belittling of empirical study’ (Schyfter 2018, 12). This might be true if Heidegger had offered a theory-centred account of science. But he did not. Heidegger argued that what was decisive in the Scientific Revolution was, as I put it, ‘not that facts, experiments, calculation and measurement are deployed, but how and to what end they are deployed’ (Kochan 2017, 233).

According to Heidegger, in the 17th c. the reciprocal relation between metaphysical projection and work experience was mathematicised. As the projection became more narrowly specified – i.e., axiomatised – the manner in which things were experienced and worked with also became narrower. In turn, the more accustomed subjects became to experiencing and working with things within this mathematical frame, the more resolutely mathematical the projection became. Mathēsis is a kind of positive feedback loop at the existential level.

Giving Heidegger Empirical Feet

This is all very abstract. That is why I suggested that ‘[a]dditional material from the history of science will allow us to develop and refine Heidegger’s account of modern science in a way which he did not’ (Kochan 2017, 235). This empirical refinement and development takes up almost all of Chapters 5 and 6, wherein I consider: studies of diagnostic method by Renaissance physician-professors at the University of Padua, up until their appointment of Galileo in 1591; the influence of artisanal and mercantile culture on the development of early-modern scientific methods, with a focus on metallurgy; and the dispute between Robert Boyle and Francis Line in the mid-17th c. over the experimentally based explanation of suction.

As Paolo Palladino recognises in his review of Science as Social Existence, this last empirical case study offers a different account of events than was given by Steven Shapin and Simon Schaffer in their classic 1985 book Leviathan and the Air-Pump, which influentially applied Edinburgh School methods to the history of science (Palladino 2018, 42). I demonstrate that Heidegger’s account is compatible with this sociological account, and that it also offers different concepts leading to a new interpretation.

Finally, at the end of Chapter 6, I demonstrate the compatibility of Heidegger’s account of modern science with Bloor’s concept of ‘social imagery,’ not just further developing and refining Heidegger’s account of modern science, but also helping to more precisely define the scope of application of Bloor’s valuable methodological concept. Perhaps this does not amount to very much in the big picture, but it is surely more than a mere ‘semantic reformulation of Heidegger’s ideas,’ as Schyfter suggests (Schyfter 2018, 13).

Given all of this, I am left a bit baffled by Schyfter’s claims that I ‘belittle’ empirical methods, that I ‘do[] not present any analysis of SSK methodologies,’ and that I am guilty of ‘a general disregard for scientific practice’ (Schyfter 2018, 12, 11).

Saving an Edinburgh School Method

Let me pursue the point with another example. A key methodological claim of the Edinburgh School is that scientific theory is underdetermined by empirical data. In order to properly explain theory, one must recognise that empirical observation is an interpretative act, necessarily (but not sufficiently) guided by social norms.

I discuss this in Chapter 3, in the context of Bloor’s and Bruno Latour’s debate over another empirical case study from the history of science, the contradictory interpretations given by Robert Millikan and Felix Ehrenhaft of the natural phenomena we now call ‘electrons.’

According to Bloor, because Millikan and Ehrenhaft both observed the same natural phenomena, the divergence between their respective claims – that electrons do and do not exist – must be explained by reference to something more than those phenomena. This ‘something more’ is the divergence in the respective social conditions guiding Millikan and Ehrenhaft’s interpretations of the data (Kochan 2017, 124-5; see also Kochan 2010, 130-33). Electron theory is underdetermined by the raw data of experience. Social phenomena, or ‘social imagery,’ must also play a role in any explanation of how the controversy was settled.

Latour rejects underdetermination as ‘absurd’ (Kochan 2017, 126). This is part of his more general dismissal of the Edinburgh School, based on his exploitation of vulnerabilities in their lingering adherence to the glass-bulb model of subjectivity. I suggest that the Edinburgh School, by fully replacing the glass-bulb model with Heidegger’s model of the subject as being-in-the-world, can deflect Latour’s challenge, thus saving underdetermination as a methodological tool.

This would also allow the Edinburgh School to preserve subjectivity as a methodological resource for sociological explanation. Like Heidegger’s metaphysical projection, the Edinburgh School’s social imagery plays a necessary (but not a sufficient) role in guiding the subject’s interpretation of natural phenomena.

The ‘Tradition’ of SSK – Open or Closed?

Earlier, I mentioned the curious fact that Schyfter never uses the word ‘subject’ or its cognates. It is also curious that he neglects my discussion of the Bloor-Latour debate and never mentions underdetermination. In Chapter 7 of Science as Social Existence, I argue that Latour, in his attack on the Edinburgh School, seeks to suppress subjectivity as a topic for sociological analysis (Kochan 2017, 353-54, and, for methodological implications, 379-80; see also Kochan 2015).

More recently, in my response to Sassower, I noted the ongoing neglect of the history of disciplinary contestation within the field of science studies (Kochan 2018, 40). I believe that the present exchange with Schyfter nicely exemplifies that internal contestation, and I thank him for helping me to more fully demonstrate the point.

Let me tally up. Schyfter is silent on the topic of subjectivity. He is silent on the Bloor-Latour debate. He is silent on the methodological importance of underdetermination. And he tries to divert attention from his silence with specious accusations that, in Science as Social Existence, I belittle empirical research, that I disregard scientific practice, that I fail to recognise the importance of social accounts of knowledge, and that I generally do not take seriously Edinburgh School methodology.

Schyfter is eager to exclude me from what he calls the ‘tradition’ of SSK (Schyfter 2018, 13). He seems to view tradition as a cleanly bounded and internally cohesive set of ideas and doings. By contrast, in Science as Social Existence, I treat tradition as a historically fluid range of intersubjectively sustained existential possibilities, some inevitably vying against others for a place of cultural prominence (Kochan 2017, 156, 204f, 223, 370f). Within this ambiguously bounded and inherently fricative picture, I can count Schyfter as a member of my tradition.

Acknowledgement

My thanks to David Bloor and Martin Kusch for sharing with me their thoughts on Schyfter’s review. The views expressed here are my own.

Contact details: jwkochan@gmail.com

References

Bloor, David (2001). ‘What Is a Social Construct?’ Facta Philosophica 3: 141-56.

Kochan, Jeff (2018). ‘On the Sociology of Subjectivity: A Reply to Raphael Sassower.’ Social Epistemology Review and Reply Collective 7(5): 39-41. https://wp.me/p1Bfg0-3Xm

Kochan, Jeff (2017). Science as Social Existence: Heidegger and the Sociology of Scientific Knowledge (Cambridge: Open Book Publishers). http://dx.doi.org/10.11647/OBP.0129

Kochan, Jeff (2015). ‘Putting a Spin on Circulating Reference, or How to Rediscover the Scientific Subject.’ Studies in History and Philosophy of Science 49:103-107. https://doi.org/10.1016/j.shpsa.2014.10.004

Kochan, Jeff (2010). ‘Contrastive Explanation and the “Strong Programme” in the Sociology of Scientific Knowledge.’ Social Studies of Science 40(1): 127-44. https://doi.org/10.1177/0306312709104780

Palladino, Paolo (2018). ‘Heidegger Today: On Jeff Kochan’s Science and Social Existence.’ Social Epistemology Review and Reply Collective 7(8): 41-46.

Sassower, Raphael (2018). ‘Heidegger and the Sociologists: A Forced Marriage?’ Social Epistemology Review and Reply Collective 7(5): 30-32.

Schyfter, Pablo (2018). ‘Inaccurate Ambitions and Missing Methodologies: Thoughts on Jeff Kochan and the Sociology of Scientific Knowledge.’ Social Epistemology Review and Reply Collective 7(8): 8-14.

Shapin, Steven and Simon Schaffer (1985). Leviathan and the Air-Pump: Hobbes, Boyle, and the Experimental Life (Princeton: Princeton University Press).

Author Information: Matthew R. X. Dentith, Institute for Research in the Humanities, University of Bucharest, m.dentith@episto.org.

Dentith, Matthew R. X. “Between Forteana and Skepticism: A Review of Bernard Wills’ Believing Weird Things.” Social Epistemology Review and Reply Collective 7, no. 11 (2018): 48-52.

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

Image by David Grant via Flickr / Creative Commons

 

Sometimes, when it is hard to review a book, it is tempting to turn in some kind of personal reflection, one demonstrates why the reviewer felt disconnected from the text they were reviewing. This review of Bernard N. Wills Believing Weird Things – which I received three months ago, and have spent quite a bit of time thinking about in the interim – is just such a review-cum-reflection, because I am not sure what this book is about, nor who its intended audience is.

According to the blurb on the back Believing Weird Things is a response to Michael Shermer’s Why People Believe Weird Things (Henry Holt and Company, 1997). Shermer’s book is one I know all too well, having read and reread it when I started work on my PhD. At the time the book was less than ten years old, and Shermer and his cohort of Skeptics (spelt with a ‘K’ to denote that particular brand of sceptical thought popular among (largely) non-philosophers in the U.S.) were considered to be the first and final word on the rationality (more properly, the supposed irrationality) of belief in conspiracy theories.

Given I was working on a dissertation on the topic, getting to grips with the arguments against belief in such theories seemed crucial, especially given my long and sustained interest in the what you might call the contra-philosophy of Skepticism, the work of Charles Fort.

Times for the Fortean

Fort (who Wills mentions in passing) was a cantankerous collector and publisher of strange and inconvenient phenomena. His Book of the Damned (Boni and Liveright, 1919) is an early 20th Century litany of things which seemed to fall outside the systemic study of the world. From rains of frogs, to cities floating in the sky, Fort presented the strange and the wonderful, often without comment. When he did dare to theorise about the phenomena he cataloged, he often contradicted his previous theories in favour of new ones. Scholars of Fort think his lack of a system was quite deliberate: Fort’s damned data was meant to be immune to scientific study.

Fort was hardly a known figure in his day, but his work has gained fans and adherents, who call themselves Forteans and engage in the study of Forteana. Forteans collect and share damned data, from haunted physics laboratories, to falls of angel hair. Often they theorise about what might cause these phenomena, but they also often don’t dispute other interpretations of the same ‘damned data.’

John Keel, one of the U.S.’s most famous Forteans (and who, if he did not invent the term ‘Men in Black’ at least popularised their existence), had a multitude of theories about the origin of UFOs and monsters in the backwoods of the U.S., which he liberally sprinkled throughout his works. If you challenged Keel on what you thought was an inconsistency of thought he would brush it off (or get angry at the suggestion he was meant to consistent in the first place).

I was a fan of Forteana without being a Fortean: I fail the Fortean test of tolerating competing hypotheses, preferring to stipulate terms whilst encouraging others to join my side of the debate. But I love reading Forteana (it is a great source of examples for the social epistemologist), and thinking about alternative interpretations. So, whilst I do not think UAP (unexpected aerial phenomena – the new term for UFO) are creatures from another dimension, I do like thinking about the assumptions which drive such theories.

Note here that I say ‘theories’ quite deliberately: any student of Forteana will quickly become aware that modern Forteans (contra Fort himself) are typically very systematic about their beliefs. It is just that often the Fortean is happy to be a systemic pluralist, happily accepting competing or complimentary systems as equally possible.

Weird and Weirder

Which brings me back to Believing Weird Things. The first section concerns beliefs people like Shermer might find weird but Wills argues are reasonable in the context under which they developed. Wills’ interest here is wide, taking in astrology, fairies, and why he is not a Rastafarian. Along the way he contextualises those supposedly weird beliefs and shows how, at certain times or in certain places, they were the product of a systemic study of the world.

Wills points out that a fault of Skepticism is a lack of appreciation for history: often what we now consider rational was once flimflam (plate tectonics), and what was systemic and rational (astrology) is today’s quackery. As Wills writes:

The Ancients do not seem to me to be thinking badly so much as thinking in an alien context and under different assumptions that are too basic to admit evaluation in the ordinary empirical sense (which is not to say they admit of no evaluation whatsoever). Further, there are many things in Aristotle and the Hebrew Bible which strike me as true even though the question of ‘testing’ them scientifically and ‘skeptically’ is pretty much meaningless. In short, the weird beliefs I study are at minimum intelligible, sometimes plausible and occasionally true. [4]

Indeed, the very idea which underpins Shermer’s account, ‘magical thinking,’ seems to fail the skeptical test: why, like Shermer, would you think it is some hardwired function rather than culturally situated? But more importantly, how is magical thinking any different from any other kind of thinking?

This last point is important because, as others have argued (including myself) many beliefs people think are problematic are, when looked at in context with other beliefs, either not particularly problematic, or no more problematic than the beliefs we assume are produced rationally. The Psychology of Religion back in the early 20th Century is a good example of this: when psychologists worried about religious belief started looking at the similarities in belief formation between the religious and the non-religious, they started to find the same kind of ‘errors’ in irreligious people as well.

In the same respect, the work in social psychology on belief in conspiracy theories seems to be suffering the same kind of problem today: it’s not clear that conspiracy theorists are any less (or more) rational than the rest of us. Rather, often what marks out the difference in belief are the different assumptions about how the world is, or how it works. Indeed, as Wills writes:

Many weird ideas are only weird from a certain assumed perspective. This is important because this assumed perspective is often one of epistemic and social privilege. We tend to associate weird ideas with weird people we look down upon from some place of superior social status. [10]

The first section of Believing Weird Things is, then, possibly the best defence of a kind of Fortean philosophy one could hope for. Yet that is also an unfair judgement, because thinking of Believing Weird Things as a Fortean text is just my imposition: Fort is mentioned exactly once, and only in a footnote. I am only calling this a tentatively Fortean text because I am not sure who the book’s audience is. Ostensibly – at least according to the blurb – it is meant to be a direct reply to Shermer’s Why People Believe Weird Things. But if it is, then it is twenty years late: Why People Believe Weird Things was published in 1997.

Not just that, but whilst Believing Weird Things deals with a set of interesting issues Shermer did not cover (yet ought to have), almost everything which makes up the reply to Why People Believe Weird Things is to be found in the Introduction alone. Now, I’d happily set the Introduction as a reading in a Critical Thinking class or elementary Epistemology class. However, I could not see much use in setting the book as a whole.

What’s Normal Anyway?

Which brings us to the second half of Believing Weird Things. Having set out why some weird beliefs are not that weird when thought about in context, Wills sets out his reasons for thinking that beliefs which aren’t – in some sense – considered weird ought to be. The choice of topics here is interesting, covering Islamophobia, white privilege, violence and the proper attitude towards tolerance and toleration in our polities.

But it invites the question (again) of who his intended audience is meant to be? For example, I also think Islamophobia, racism, and violence are deeply weird, and it worries me that some people still think they are sensible responses. But if Wills is setting out to persuade the other half of the debate, the racists, the bigots, and the fans of violence, then I do not think he will have much luck, as his discussions never seem to get much further than “Here are my reckons!”

And some of those reckons really need more arguments in favour of them.

For example, Wills brings out the old canard that religious beliefs and scientific beliefs are one and the same (presented as ‘religious faith’ and ‘scientific faith’). Not just that, but, in chapter 6, he talks about the things ‘discovered’ by religion. These are presented as being en par with discoveries in the sciences. Yet aren’t the things discovered by religion (‘humans beings must suffer before they learn. … existence is suffering’ [48]) really the ‘discoveries’ of, say, philosophers working in a religious system? And aren’t many of these discoveries just stipulations, or religious edicts?

This issue is compounded by Wills specification that the process of discovery for religious faith is hermeneutics: the interpretation of religious texts. But that invites even more questions: if you think the gods are responsible for both the world and certain texts in the world you could imagine hermeneutic inquiry to be somehow equivalent to scientific inquiry, but if you are either doubtful of the gods, or doubtful about the integrity of the gods’ prophets, then there is much room to doubt there is much of a connection at all between ‘faith’ in science and faith in scripture.

Another example: in chapter 8, Wills states:

Flat-Earthers are one thing but Birthers, say, are quite another: some ideas do not come from a good place and are not just absurd but pernicious. [67]

Now, there is an argument to be had about the merits (or lack thereof) of the Flat Earth theory and the thesis Barack Obama was not born in the U.S. Some might even claim that the Flat Earth theory is worse, given that belief might entail thinking a lot of very disparate institutions, located globally, are in on a massive cover-up. The idea Barack Obama is secretly Kenyan has little effect on those of us outside the U.S. electoral system.

None of this is to say there aren’t decent arguments to be had about these topics. It is, instead, to say that often these positions are stipulated. As such, the audience for Believing Weird Things seems to be people who agree with Wills, rather than an attempt by Wills to change hearts and minds.

How to Engage With Weird Beliefs

Which is not to say that the second half of the book lacks merit; it just lacks meat. The chapters on Islamophobia (chapter 8) and racism (chapter 9) are good: the contextualisation of both Islamophobia and the nature of conflicts in the Middle East are well expressed. But they are not particularly novel (especially if you read the work of left-wing commentators). But even if the chapters are agreeable to someone of a left-wing persuasion, all too often the chapters just end: the chapter on violence (chapter 10), for example, has no clear conclusion other than that violence is bad.

Similarly confused is the chapter on tolerance (chapter 11). But the worst offender is the chapter on the death of Conservatism (chapter 14). This could have been an interesting argument about the present state of today’s politics. But the chapter ends abruptly, and with it, the book. There is no conclusion, no tying together of threads. There’s hardly even any mention of Shermer or skepticism in the second half of Believing Weird Things.

Which brings us back to the question: who is this book for? If the book were just the first half it could be seen as both a reply to Shermer and a hesitant stab at a Fortean philosophy. But the second half of the book comes across more as the author’s rumination on some pertinent social issues of the day, and none of that content seems to advance far beyond ‘Here are my thoughts…’

Which, unfortunately, is also the character of this review: in trying to work out who the book is for I find my thoughts as inconclusive as the text itself. None of this is to say that Believing Weird Things is a bad or terrible book. Rather, it is just a collection of the author’s ruminations. So, unless you happen to be a fan of Wills, there is little to this text which substantially advances the debate over belief in anything.

Contact details: m.dentith@episto.org

References

Fort, Charles. The Book of the Damned, Boni and Liveright, 1919

Shermer, Michael. Why People Believe Weird Things, Henry Holt and Company, 1997

Wills, Bernard N. Believing Weird Things, Minkowski Institute Press, 2018

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

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

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

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

 

This essay is in reply to:

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

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

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

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

Creeping Colonialism in Science

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

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

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

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

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

Precious Signs of Hope Amid Conflict

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

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

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

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

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

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

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

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

Overcoming a Rational Suspicion

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

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

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

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

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

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

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

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

When Seeds Are Planted, Change Can Come

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

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

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

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

Contact details: jwkochan@gmail.com

References

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

Author Information: Nuria Anaya-Reig, Universidad Rey Juan Carlos, nuria.anaya@urjc.es

Anaya-Reig, Nuria. “Teorías Implícitas del Investigador: Un Campo por Explorar Desde la Psicología de la Ciencia.” Social Epistemology Review and Reply Collective 7, no. 11 (2018): 36-41.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-434

Image by Joan via Flickr / Creative Commons

 

This article is a Spanish-language version of Nuria Anaya-Reig’s earlier contribution, written by the author herself:

Anaya-Reig, Nuria. “Implicit Theories Influencing Researchers: A Field for the Psychology of Science to Explore.” Social Epistemology Review and Reply Collective 7, no. 11 (2018): 25-30.

¿Qué concepciones tienen los investigadores sobre las características que debe reunir un estudiante para ser considerado un potencial buen científico? ¿En qué medida influyen esas creencias en la selección de candidatos? Estas son las preguntas fundamentales que laten en el trabajo de Caitlin Donahue Wylie (2018). Mediante un estudio cualitativo de tipo etnográfico, se entrevista a dos profesores de ingeniería en calidad de investigadores principales (IP) y a estudiantes de sendos grupos de doctorado, la mayoría graduados, como investigadores noveles. En total, la muestra es de 27 personas.

Los resultados apuntan a que, entre este tipo de investigadores, es común creer que el interés, la asertividad y el entusiasmo por lo que se estudia son indicadores de un futuro buen investigador. Además, los entrevistados consideran que el entusiasmo está relacionado con el deseo de aprender y la ética en el trabajo. Finalmente, se sugiere una posible exclusión no intencional en la selección de investigadores a causa de la aplicación involuntaria de sesgos por parte del IP, relativa a la preferencia de características propias de grupos mayoritarios (tales como etnia, religión o sexo), y se proponen algunas ideas para ayudar a minimizarlos.

Teorías Implícitas en los Sótanos de la Investigación

En esencia, el trabajo de Wylie (2018) muestra que el proceso de selección de nuevos investigadores por parte de científicos experimentados se basa en teorías implícitas. Quizás a simple vista puede parecer una aportación modesta, pero la médula del trabajo es sustanciosa y no carece de interés para la Psicología de la Ciencia, al menos por tres razones.

Para empezar, porque estudiar tales cuestiones constituye otra forma de aproximarse a la compresión de la psique científica desde un ángulo distinto, ya que estudiar la psicología del científico es uno de los ámbitos de estudio centrales de esta subdisciplina (Feist 2006). En segundo término, porque, aunque la pregunta de investigación se ocupa de una cuestión bien conocida por la Psicología social y, en consecuencia, aunque los resultados del estudio sean bastante previsibles, no dejan de ser nuevos datos y, por tanto, valiosos, que enriquecen el conocimiento teórico sobre las ideas implícitas: es básico en ciencia, y propio del razonamiento científico, diferenciar teorías de pruebas (Feist 2006).

En último lugar, porque la Psicología de la Ciencia, en su vertiente aplicada, no puede ignorar el hecho de que las creencias implícitas de los científicos, si son erróneas, pueden tener su consiguiente reflejo negativo en la población de investigadores actual y futura (Wylie 2018).

Ya Santiago Ramón y Cajal, en su faceta como psicólogo de la ciencia (Anaya-Reig and Romo 2017), reflexionaba sobre este asunto hace más de un siglo. En el capítulo IX, “El investigador como maestro”, de su obra Reglas y consejos sobre investigación científica (1920) apuntaba:

¿Qué signos denuncian el talento creador y la vocación inquebrantable por la indagación científica?

Problema grave, capitalísimo, sobre el cual han discurrido altos pensadores e insignes pedagogos, sin llegar a normas definitivas. La dificultad sube de punto considerando que no basta encontrar entendimientos perspicaces y aptos para las pesquisas de laboratorio sino conquistarlos definitivamente para el culto de la verdad original.

Los futuros sabios, blanco de nuestros desvelos educadores, ¿se encuentran por ventura entre los discípulos más serios y aplicados, acaparadores de premios y triunfadores en oposiciones?

Algunas veces, sí, pero no siempre. Si la regla fuera infalible, fácil resultara la tarea del profesor, bastaríale dirigirse a los premios extraordinarios de la licenciatura y a los números primeros de las oposiciones a cátedras. Mas la realidad se complace a menudo en burlar previsiones y malograr esperanzas. (Ramón y Cajal 1920, 221-222)

A Vueltas con las Teorías Implícitas

Recordemos brevemente que las teorías ingenuas o implícitas son creencias estables y organizadas que las personas hemos elaborado intuitivamente, sin el rigor del método científico. La mayoría de las veces se accede a su contenido con mucha dificultad, ya que la gente desconoce que las tiene, de ahí su nombre. Este hecho no solo dificulta una modificación del pensamiento, sino que lleva a buscar datos que confirmen lo que se piensa, es decir, a cometer sesgos confirmatorios (Romo 1997).

Las personas vamos identificando y organizando las regularidades del entorno gracias al aprendizaje implícito o incidental, basado en el aprendizaje asociativo, pues necesitamos adaptarnos a las distintas situaciones a las que nos enfrentamos. Elaboramos teorías ingenuas que nos ayuden a comprender, anticipar y manejar de la mejor manera posible las variadas circunstancias que nos rodean. Vivimos rodeados de una cantidad de información tan abrumadora, que elaborar teorías implícitas, aprendiendo qué elementos tienden a presentarse juntos, constituye una forma muy eficaz de hacer el mundo mucho más predecible y controlable, lo que, naturalmente, incluye el comportamiento humano.

De hecho, el contenido de las teorías implícitas es fundamentalmente de naturaleza social (Wegner and Vallacher 1977), como muestra el hecho de que buena parte de ellas pueden agruparse dentro las llamadas Teorías Implícitas de la Personalidad (TIP), categoría a la que, por cierto, bien pueden adscribirse las creencias de los investigadores que nos ocupan.

Las TIP se llaman así porque su contenido versa básicamente sobre cualidades personales o rasgos de personalidad y son, por definición, idiosincráticas, si bien suele existir cierta coincidencia entre los miembros de un mismo grupo social.

Entendidas de modo amplio, pueden definirse como aquellas creencias que cada persona tiene sobre el ser humano en general; por ejemplo, pensar que el hombre es bueno por naturaleza o todo lo contrario. En su acepción específica, las TIP se refieren a las creencias que tenemos sobre las características personales que suelen presentarse juntas en gente concreta. Por ejemplo, con frecuencia presuponemos que un escritor tiene que ser una persona culta, sensible y bohemia (Moya 1996).

Conviene notar también que las teorías implícitas se caracterizan frente a las científicas por ser incoherentes y específicas, por basarse en una causalidad lineal y simple, por componerse de ideas habitualmente poco interconectadas, por buscar solo la verificación y la utilidad. Sin embargo, no tienen por qué ser necesariamente erróneas ni inservibles (Pozo, Rey, Sanz and Limón 1992). Aunque las teorías implícitas tengan una capacidad explicativa limitada, sí tienen capacidad descriptiva y predictiva (Pozo Municio 1996).

Algunas Reflexiones Sobre el Tema

Científicos guiándose por intuiciones, ¿cómo es posible? Pero, ¿por qué no? ¿Por qué los investigadores habrían de comportarse de un modo distinto al de otras personas en los procesos de selección? Se comportan como lo hacemos todos habitualmente en nuestra vida cotidiana con respecto a los más variados asuntos. Otra manera de proceder resultaría para cualquiera no solo poco rentable, en términos cognitivos, sino costoso y agotador.

A fin de cuentas, los investigadores, por muy científicos que sean, no dejan de ser personas y, como tales, buscan intuitivamente respuestas a problemas que, si bien condicionan de modo determinante los resultados de su labor, no son el objeto en sí mismo de su trabajo.

Por otra parte, tampoco debe sorprender que diferentes investigadores, poco o muy experimentados, compartan idénticas creencias, especialmente si pertenecen al mismo ámbito, pues, según se ha apuntado, aunque las teorías implícitas se manifiestan en opiniones o expectativas personales, parte de su contenido tácito es compartido por numerosas personas (Runco 2011).

Todo esto lleva, a su vez, a hacer algunas otras observaciones sobre el trabajo de Wylie (2018). En primer lugar, tratándose de teorías implícitas, más que sugerir que los investigadores pueden estar guiando su selección por un sesgo perceptivo, habría que afirmarlo. Como se ha apuntado, las teorías implícitas operan con sesgos confirmatorios que, de hecho, van robusteciendo sus contenidos.

Otra cuestión es preguntarse con qué guarda relación dicho sesgo: Wylie (2018) sugiere que está relacionado con una posible preferencia por las características propias de los grupos mayoritarios a los que pertenecen los IP basándose en algunos estudios que han mostrado que en ciencia e ingeniería predominan hombres, de raza blanca y de clase media, lo que puede contribuir a recibir mal a aquellos estudiantes que no se ajusten a estos estándares o que incluso ellos mismos abandonen por no sentirse cómodos.

Sin duda, esa es una posible interpretación; pero otra es que el sesgo confirmatorio que muestran estos ingenieros podría deberse a que han observado esos rasgos las personas que han  llegado a ser buenas en su disciplina, en lugar de estar relacionado con su preferencia por interactuar con personas que se parecen física o culturalmente a ellos.

Es oportuno señalar aquí nuevamente que las teorías implícitas no tienen por qué ser necesariamente erróneas, ni inservibles (Pozo, Rey, Sanz and Limón 1992). Es lo que ocurre con parte de las creencias que muestra este grupo de investigadores: ¿acaso los científicos, en especial los mejores, no son apasionados de su trabajo?, ¿no dedican muchas horas y mucho esfuerzo a sacarlo adelante?, ¿no son asertivos? La investigación ha establecido firmemente (Romo 2008) que todos los científicos creativos muestran sin excepción altas dosis de motivación intrínseca por la labor que realizan.

Del mismo modo, desde Hayes (1981) sabemos que se precisa una media de 10 años para dominar una disciplina y lograr algo extraordinario. También se ha observado que muestran una gran autoconfianza y que son espacialmente arrogantes y hostiles. Es más, se sabe que los científicos, en comparación con los no científicos, no solo son más asertivos, sino más dominantes, más seguros de sí mismos, más autónomos e incluso más hostiles (Feist 2006). Varios trabajos, por ejemplo, el de Feist y Gorman (1998), han concluido que existen diferencias en los rasgos de personalidad entre científicos y no científicos.

Pero, por otro lado, esto tampoco significa que las concepciones implícitas de la gente sean necesariamente acertadas. De hecho, muchas veces son erróneas. Un buen ejemplo de ello es la creencia que guía a los investigadores principales estudiados por Wylie para seleccionar a los graduados en relación con sus calificaciones académicas. Aunque dicen que las notas son un indicador insuficiente, a continuación matizan su afirmación: “They believe students’ demonstrated willingness to learn is more important, though they also want students who are ‘bright’ and achieve some ‘academic success.’” (2018, 4).

Sin embargo, la evidencia empírica muestra que ni las puntuaciones altas en grados ni en pruebas de aptitud predicen necesariamente el éxito en carreras científicas (Feist 2006) y que el genio creativo no está tampoco necesariamente asociado con el rendimiento escolar extraordinario y, lo que es más, numerosos genios han sido estudiantes mediocres (Simonton 2006).

Conclusión

La Psicología de la Ciencia va acumulando datos para orientar en la selección de posibles buenos investigadores a los científicos interesados: véanse, por ejemplo, Feist (2006) o Anaya-Reig (2018). Pero, ciertamente, a nivel práctico, estos conocimientos serán poco útiles si aquellos que más partido pueden sacarles siguen anclados a creencias que pueden ser erróneas.

Por tanto, resulta de interés seguir explorando las teorías implícitas de los investigadores en sus diferentes disciplinas. Su explicitación es imprescindible como paso inicial, tanto para la Psicología de la Ciencia si pretende que ese conocimiento cierto acumulado tenga repercusiones reales en los laboratorios y otros centros de investigación, como para aquellos científicos que deseen adquirir un conocimiento riguroso sobre las cualidades propias del buen investigador.

Todo ello teniendo muy presente que la naturaleza implícita de las creencias personales dificulta el proceso, porque, como se ha señalado, supone que el sujeto entrevistado desconoce a menudo que las posee (Pozo, Rey, Sanz and Limón 1992), y que su modificación requiere, además, un cambio de naturaleza conceptual o representacional (Pozo, Scheuer, Mateos Sanz and Pérez Echeverría 2006).

Por último, tal vez no sea razonable promover entre todos los universitarios de manera general ciertas habilidades, sin tener en consideración que reúnen determinados atributos. Por obvio que sea, hay que recordar que los recursos educativos, como los de cualquier tipo, son necesariamente limitados. Si, además, sabemos que solo un 2% de las personas se dedican a la ciencia (Feist 2006), quizás valga más la pena poner el esfuerzo en mejorar la capacidad de identificar con tino a aquellos que potencialmente son válidos. Otra cosa sería como tratar de entrenar para cantar ópera a una persona que no tiene cualidades vocales en absoluto.

Contact details: nuria.anaya@urjc.es

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