What if the hospital offered you the chance to make a few DNA tweaks that could ensure your children will live happily ever after? Would you recoil in horror, or jump at the chance? If you could turn back the clock would you choose to remove pain, worry, and anxiety from your own blueprint? Would you be you, or a better you, for undergoing such tweaks?
Few questions are more momentous. From Brave New World (1932) to Gattaca (1998) science fiction has flirted with making people incapable of experiencing bodily pain and psychological suffering, through cut-and-pasting the human genome in ways that render happiness a default precondition. Nonetheless, such sci-fi thought experiments imbibe a moral tale, too: for all such utopianism, dystopia emerges. In Brave New World, characters take mood brightener pills, Soma, yet still feel bad emotions and so need to take mood brighteners at all. Meanwhile, in Gattaca, a silver of discontent and resistance propels the lead character to prove the dystopian—and upgraded—intelligentsia wrong in believing that talent depends on genes. Nonetheless, such fiction might mislead us. No amount of effort could enable the lead character in Gattaca to outperform a rival who puts in the same amount of effort but has—an effort being equal—genes better suited to his task; just as no amount of ‘meritocratic’ effort can render height trivial in basketball. For an alternative analogy, more pertinent to wellbeing: consider that being able to endure stormy seas depends on the constitution of the ship as much as sailor management skills; sailors not having to worry about stormy seas at all, or at least far less, has its ethical appeal just as depressives not having to manage their moods does.
Happiness does co-depend on genes; in the pie-chart of lifestyle changes and genetic inheritance, genetics boasts the major share. Think of how inheritable depression is, despite favourable circumstances, for proof of concept. Intervening to tweak, avert, or mitigate such wellbeing genes may be more ethical than inaction. Contrary to science fiction dramas where pain, suffering, and reversals are necessary to human growth and flourishment—the real world offers a different picture. Persons live with congenital insensitivity to pain (CIP), for example, whereby they never feel hurt. Persons with CIP have been known to bite their tongues off, singe their skin, pull their eyelashes out with tweezers, and sometimes jump off buildings. Few make it through life unscathed. Children with pain insensitivity are known to still suffer and cry, for example, if a beloved pet runs away, or over the suicide of a brother, or even upon hearing a sad story. Steven Pete, who has CIP, laments his painless condition, saying: “I hope that one day parents will be able to make a choice for their children who don’t feel pain, to activate that sodium channel so that their children can live a normal life.” Rather than activate the channel, however, the research community seeks to imitate the condition in others and block the sodium channel—to create incredible painkillers for the 1.9bn who suffer recurrent tension headaches. A Stanford university-affiliated think tank, Invincible Wellbeing, meanwhile aims to end suffering through biotechnology.
Its co-founder David Pearce, has argued that we should wield our incipient knowledge to run control trials on CRISPR-Cas-9 modified twins to test what gene profiles are likely to make life less painful, perhaps even non-painful. Tweaking the genetic profile, Pearce says, is wise since children are born into the world via a genetic roulette already, without human intervention. Seeing how to make more winners in that genetic roulette game—and who wouldn’t count people who enjoy life more as winners?—is an ethical demand. I am sympathetic to the mission of mitigating suffering, for example, in identifying what allows 7-8% of people to live life without headaches, and on consensually altering genes for treatment-resistantdepression. Nevertheless, the boldness in ‘eliminating suffering’ puts me off. As does the transhumanist mania of Pearce’s book, The Hedonistic Imperative(that like the Oxford University Press published Human Enhancement) raises numerous red flags that point towards eugenics, inequality, and technophilic hubris. A Frankenstein technophilic hubris that comes from not working on any technological projects firsthand. As the real-world example of Steven Pete shows, moreover, some people can feel no pain due to gene variants, but still, suffer. Pain and suffering differ in kind as well as degree.
We must confront the fact, then, that there is no single substrate – origin point, substance, or whatever – for suffering in bodies. Neurochemical and environmental interactions are tremendously complex; having a body minus any suffering, undesirable affect, or decay is as impossible as having a mind without a body. As biologist Richard Lewontin noted in The Third Helix and Biology as Ideology, making changes in dynamic systems is fraught with challenges: removing one gene might have synergistic and unwanted effects that are off the map. Reducing the risk of heart disease, say, but raising the risk of diabetes. Especially given how shared human DNA is with microbial life (and there are around 500 million neurons in the gut) human engineering is the opposite of an easy fix. New solutions, make new problems; a mission to end suffering by these lights is infeasible at best and distracts from other proven methods like making environments better for whatever genes you have, at worst.
But I tempered this belief after I came across the story of Jo Cameron. Her story challenged my beliefs and reading of the available evidence.
Jo Cameron, a Scottish woman studied by a University College London genetics team, offers an example of a life without pain and with ‘productive’ suffering. Her mother’s death and her son’s hospitalisation never got her down; she herself has had few injuries. As Cameron says, “in fact, I never worry about anything”. Why? A small deletion in her FAAH gene (misleadingly named a ‘pseudogene’) renders her painless and, so the theory goes, her raised amounts of amadadine give her a permanently sunny disposition. Incredible. Such a minature change can alter her whole life? It’s both surprising and predictable. Let us consider a brief menu of genes, their emotional effects, and a particularly emotional brain region. Feel free to skip the following, more technical, paragraph if you prefer.
FAAH-OUT, SCNA-9, COMT, 5-HTTLPR, and ADRA2B. Otherwise known by their catchy names: fatty acid amide hydrolase, sodium voltage-gated channel alpha subunit 9, catechol O methyltransferase Val158Met, serotonin transporter gene linked polymorphic region, and adrenoceptor alpha 2B. A small deletion in FAAH renders its owners painless; one mutation variant in SCNA-9 renders pain insensitivity while another mutant variant renders pain hypersensitivity; the number of MET alleles (versions of genes) in COMT bustresses reward, with more MET versions meaning more reward felt; 5-HTTLPR renders peculiar susceptibility to stress-induced depression; ADRA2b with some ‘standard’ amino acids missing makes traumatic memories more intrusive than those with the ‘standard’ amino acids present but similar-enough adverse experience. More blunt means to remove negative emotions include removing the amygdala – cutting away part of the lower brain, in a surgery named amygdalectomy – that cuts away fear and anxiety. At the price of reduced brain functions, surgery risk, and social skill impairments. Amygda-less patients suffused with CO2, moreover show fear and panic, defeating the simplistic view that fear and panic emanate from the amygdala alone.
So, being able to feel a different range of emotions because of brain and gene changes makes sense, and is even predictable. Given the number of genes it also makes sense that miniature changes can have sizable effects down the line. What is most surprising is how Jo Cameron feels no pain whilst suffering only ephemeral and proportional moods. My intuition suggests far more is going on in her biology and circumstances than FAAH-OUT (Cameron is, for instance, forgetful) but it is a proof of concept that minimising suffering through changed genes is possible. Afterall, it has already happened in Jo, her son, and inferably in less eminent cases than theirs.
The roots of suffering are many, and I wish to dissuade anyone who wants a biological solution to social problems. For instance researchers who suggest Danish DNA may be the secret to happiness by assuming that controlling for culture, welfare states, and transgenerational epigenetic trauma, is feasible, when in reality, favourable circumstances for the genes’ carriers is the most tenable explanation.
Suffering workplace stress that induces depression, for a hypothetical instance, demands that workplaces become less stressful rather than genetic constitutions more resilient to working stressful hours; opioid crises that stem from low-social status and isolation demand equity and community; ethical care for animals means not eating them rather than editing their genomes – without any deliberation on their part – to exhibit no pain symptoms. All that said, nonetheless, research into the biological substrates of suffering—such as what makes Jo Cameron different from her pain-feeling family, what makes people ruminate more and others not, all else equal—will be a genuine revolution in human flourishing. A revolution that is desirable so long as citizens are able to deliberate what makes the agenda and what technological advances to reject for being too regressive or too dangerous. Invincible Wellbeing is doing its part— coordinating research projects, funding researchers, and offering a $100k prize for the best research project—to bring a wellbeing revolution to sufferers of chronic pain and needless malaise. Such a project, though, is a drop in the ocean for deciding how to best allow human flourishing and may actually detract from more tenable means to alleviate suffering, such as with welfare reforms, seen in nations that come out top in the United Nations’ Human Development Index.
Nonetheless, the choice between social planning and genetic ramifications are no longer opposites. As the behavioural geneticist Kathryn Paige Harden argues, for the comprehensive delivery of equality, ethically wielded genomics and concepts may be an asset. Claims to, for example, deserved wealth as in the case of Bill Gates, are diminished in light of a high-IQ gene-profile paired with a high-income household (his mother worked for IBM and sparked inicpient interest and ample opportunity in computers).
To conclude, then, suffering is not as inevitable as we think—from social and biological and pharmacological interventions, suffering can be diminished, and pain even – should we wish it – be eliminated.
Just what does the future hold? The potential futures of pain and suffering biotechnology research are scintillating and terrifying at the same time.
I argue that innovation policy is in the process of being re-characterised as a joint venture of public-private enterprise with justification from government found in rhetoric for innovation to overcome Grand Challenges. To demonstrate my thesis, I will consider how the United Kingdom Research and Innovation (UKRI) policy works: the objectives, policies, institutions, and funding bodies involved, what incentives are offered, and how funds are distributed. I will critique and contextualise this new, supposedly statist, policy regime “where profit seeking entrepreneurs as well as an entrepreneurial state” are policy axioms.
How the UKRI functions
On the advice of Sir Paul Nurse’s 2014 report, the government merged the following research councils to form the UKRI: theArts and Humanities Research Council (ARHC), Biotechnology and Biological Sciences Research Council (BBSRC), Engineering and Physical Sciences Research Council (EPy FRSC), Economic and Social Research Council (ESRC), Medical Research Council (MRC), Natural Environment Research Council (NERC), Science Technology Facilities (STFC), Innovate UK, and Research England. The seat of authority and funding for all of these councils is in Whitehall at the Department for Business, Energy, and Industrial Strategy (BEIS). The concerted effort of BEIS in influencing the direction of research councils’ priorities and objectives exemplifies the recent re-charateristion of innovation policy: historically, research councils were left to innovate and share of their own accord, in line with the Haldane Principle whereby politicians never sway researchers’ objectives. The onus is now placed into a national effort and moonshots. Despite embracing Haldane in Principle the new arrangement corners councils into obeying BEIS goals in practice; with the Secretary of State entitled to attendance and all materials except the lower executive committees; the UKRI CEO entitled to lead the executive committee and chair the board. The 2021 R&D roadmap, moreover, demonstrates a heavy-hand, mentioning ‘moonshot’ eleven times. The 2014 Department for Business Innovation and Skills report Our Plan For Growth: Science and Innovation meanwhile never mentions moonshots at all but soft-touch Grand Challenges instead. The ethos for state-led collaboration is present in 2014 but more modest and reserved. I quote:
It is not the job of a strategy for science and innovation that will last for 10 years to specify in detail the scientific questions to be answered. And when it comes to fundamental research it remains the case that those at the ‘coal face’ of research are best placed to identify the key questions and opportunities to advance knowledge. However, many of the ‘grand challenges’ for society, the ultimate customer for research, are obvious: developing cost effective low carbon power sources and storage solutions for energy-hungry economies; harnessing and managing scarce resources; improving human, animal and plant health.
Our Plan For Growth: Science and Innovation
A confluence of business, government, university, and think-tank advocacy is behind the change of language from hesitant ‘grand challenges’ to moonshots. Mariana Mazzucato advocated moonshots in an entrepreneurial state pamphlet for the think tank Demos in July 2011. Part of the Roadmap is the creation of an Innovation Expert Group (IEG) including Mazzucato as an adviser. In 2018, a mission orientated commission at the Institute for Innovation and Public Purpose (IIPP) “interacted directly with policy teams in BEIS to help develop these [Theresa May’s] missions into viable project plans”. And in 2014, Business Secretary Vince Cable celebrated her Entrepreneurial State citing the common ground between her facts and his policy making: the Catapult network to commercialise science-into-industry, tax incentives for R&D, public investment to solve private sector underinvestment, long-termist industrial strategy “whose commitments go much further than narrowly ‘addressing market failures’”, patient capital through the Business Bank, all feature. Vince Cable embodies the re-characterisation of UK innovation policy in one sentence: “Innovation needs a mixed economy: profit seeking entrepreneurs as well as an entrepreneurial state.” Nurse’s report and Cable’s speech formed premises which has UKRI turned into practice.
Compare the above quoted policy passage to the UK R&D Roadmap and the UKRI objectives and it demonstrates how mission-led innovation policy has become. Whereas before innovation was viewed as more local and organic, up to those at the “coal face”. Now the efforts of the roadmap and UKRI are towards Entrepreneurial State ambitions. Part of that mission is mediating the objectives, priorities, and policies for its institutions.
How UKRI uses objectives, policies, and institutions
The UKRI publishes its objectives in its Corporate Plan, Annual Report, Delivery Plans, and Five Year Plan for Sustainability, to name a few. By coordinating through documents which list objectives for each council, economic actors can decide and align their research, career, investment, and institution priorities accordingly. The list of objectives include: countering COVID-19; innovators at UN climate conference; diversity and inclusivity; humane work culture; strengthening interconnections; attracting talent; implementing human resources; fostering business-led innovation. Many of these ‘objectives’ are vague and lack rigour. For example humane work culture and inclusivity are never paired with money or affirmative action schemes. Whereas interconnectivity and talent are fostered through Knowledge Exchange Framework and Skill Visa support. The disparity in investment suggests that UKRI values business and collaboration above equity.
What flagship policies do UKRI wield to turn objectives into practice? The biggest policy is corporatisation. Whereby each council is akin to a division in the company with strategy and objectives mediated for the greater purpose and consideration of all, especially financial, stakeholders. By corporatisation I mean the new management policy and structure which models itself on corporate management. The management structure, notably without CEO and the BEIS’ Secretary of State, is illustrated below:
Policy wonks, Paul Nurse and John Kingman commend that the UKRI board is “responsible for holding the research councils, Innovate UK and Research England (the nine ‘Councils’) to account, it must be independent of them.” The function of the board is keeping funding and priorities in check. The upper management include Nominations and Remunerations, Board Investment Committee, Audit Risk and Performance Committee. This is a structure reminiscent of Bupa (a private medical company) with its Audit, Risk, Nomination & Governance committees. The UKRI upper management and board however is the same as the Wellcome Trust in name; more corporate than private companies, with its larger size, multi divisions, and investment portfolio prominence. Despite the Wellcome being a charity, and UKRI a public body, both structures have imitated industry management. The embrace of a CEO, a board, investment committee, and corporate human resources (to come), reveals business (private sector) influence. Much as the onus on business and industrial strategy in the ‘BEIS’ name implies the same.
UKRI sub-policies are also corporatised: competitiveness based grants, a massive investment portfolio, and private stakeholders. The Industrial Strategy Challenge Fund (ISCF), for example, hosts competitions for companies to suggest how they can best contribute to one of the strategy challenges and thereby gain funds; the ISCF boasts £2.6 billion in public investment and £3 billion from industry; National Research Campuses garner private investment. Corporatisation supports the argument that innovation policy encourages public-private hybridisation. Even publicly funded research institutes are industry collaborative. Not one research institute works without industry collaboration or investment and the onus in the UKRI Corporate Plan 2020-2021 is on examples where private companies and semi-private stakeholders have put in the most money. The flagship Babraham Centre, moreover, boasts stakeholders like Cambridge University and 60 bioscience companies. The Francis Crick Institute boasts stakeholders like University College London, Wellcome, Cancer Research UK, and the Medical Research Council. For the few UKRI research institutes to be networked with universities and private companies demonstrates the omnipresence of public-private hybridisation; instead of being purely state led. Even national institutes are public-private hybrids, and even partner universities and charities like UCL and Wellcome work like corportaised businesses. For example, money from international students is consumers’ money and Welcome attains revenue from its investment portfolio. With its corporate policies, incentives are also modelled on what works in business with the offer of money and prestige—“symbolic capital”—an obvious incentive to innovate. What other incentives, then, are offered?
How UKRI wields incentives
Incentives include funding, networking opportunities, and good public relations. Funding allows for new projects to be taken and secured for a long run; partnerships across institutions allows for more opportunities for funding, prestige, and efficient knowledge transfer; de-risking incentivises otherwise unappealing enterprise; working on human-need challenges is a good way to bolster a positive public relations image. To fulfill UKRI goals, however, incentives such as funding, network opportunities, de-risking, and good public relations depend on meeting UKRI goals. Those goals are thereby incentivised. For example, excellence in research for UKRI depends on a. Impact b. Commercial viability c. Openness d. Public-private co-investment. Bear in mind however that these criteria are still forming and debated. Broadly speaking, incentives entice researchers, companies, and public institutions to work on projects that have impact, start-up potential, transparency and industry-university stakes.
The UKRI creating suitable conditions and taking on much of the risk allows for businesses to comfortably join them—hence the UKRI corporate plan speaks of de-risking as a prized goal. Yet ‘de-risking’ is merely the transfer of innovation risk, as Mazzucato explains, in incentivising businesses they stand to profit whilst the state loses. All the aforementioned incentives aim to translate innovation into economic growth and effect economies of scale across the industry. The telling aim of de-risking however shows the state fails to be so entrepreneurial, instead taking on risk whilst outsourcing gains: innovation is therefore not inevitably more efficient or incentivised but often stymied in the misplaced emulation of prestigious and fashionable private institutions’ techniques. A major flaw in UKRI is not emulating where it counts: in gaining royalties to further fund innovation within public institutions. UKRI’s ESRC for example is lackadaisical about royalties; inferably, in the belief that innovation benefit diffuses through business and back to tax and thereby can fuel the innovation budget. That is a misguided belief. Patents, when protectionist, have historically stifled innovation and when private business is free to patent from the output of public endeavour they thereby stifle innovation still. Temporary patents would provide revenue for more public innovation to keep the innovation cycle re-spinning—as it already does in nations like Denmark and Germany. Whereas private patenting is liable to lead to less investment in public innovation and less investment in innovative high risk discovery at all. The history of state-led innovations like the internet, that was never capitalised on by the state, and states founding markets to begin with, attests the merit of refunding the state. The Knowledge Exchange Schemes and BEIS’s framework for UKRI nevertheless echo the ESRC diffusion proposition. The BEIS’s UKRI framework mentions intellectual property once, in a footnote—“to a lesser extent UKRI also supports commercialisation of research directly through its own IP (Intellectual Property) portfolio.” And the UKRI corporate plan mentions “intellectual property” and “patent” once, both in reference to industry collaboration and business spin-offs from academia. Research England data confirms the minor incentive of IP in UK innovation policy. “80 percent” of IP belongs to six English institutions; illustrated below:
IP assets per institution, Research England
And what is more, to incentivise excellence and innovation, excellent research and innovators must be distinguished – from mediocre research and renovators – for grant funding to be allocated. But by that very logic genuinely new innovative ground and research centres are seldom trodden or established, but old effective methods and innovation centres consolidated instead. So, how does UKRI select and invest in innovation candidates?
How UKRI distributes funds
Funds from the research and innovation budget and science infrastructure budget are portioned out to the nine councils. As shown below:
These demonstrate that Research England, Innovate UK, and EPSRC are major beneficiaries and further suggest that priorities are in seeding innovation in businesses (Innovate UK), and fostering Engineering and Physical Science (EPSRC, STFC). Meanwhile little money is apportioned to social sciences and humanities. True, sciences are literally more expensive to fund but, even with infrastructure discounted, the favour for STEM funding is evident within individual universities and within the BEIS budget. Surprisingly little goes to biotechnology (BBSRC) or medical research (MRC) perhaps because funds from the private sector and charities, such as Wellcome, bear the brunt—and innovation happens transnationally. The Financial Times (FT) issue on The Future of AI and Digital Healthcare, for example, details billions of investments from McKinsey, Amazon, and Google into UK AI in hope of innovative disruption with health providers, such as the NHS, providing data instead of money. As for biotechnology, being an emerging sector, a relatively small amount can be explained when you consider how additional funding does not automatically equate to more innovation. Indeed, the quality and suitability of funding locations and centres matters. Consider the UKRI institutes mapped below:
UKRI research institute locations
Funding allocations for research and development distributed across the UK regions appear surprisingly equitable. Northern Ireland being the greatest per-researcher benefactor, and the South East bearing more research and development expenditure than London or the East of England. However the UKRI national institutes cluster around productive urban knowledge centres. Note how concentrated the institutes are in the map above. Three centres are neighbours in one Research Park in Norwich, another three in Cambridge Research Park, in the capitals Edinburgh and London, and a belt of institutes in the north. Moreover, favourable regional distribution isn’t the same as equitable local distribution; most R&D concentrates. UKRI R&D funding positively correlates with business funding across the board. I provide 2018-2019 overview data for perusal here and a background of R&D ‘activity’, by ‘sector’, in general:
Considering the total amounts of UKRI funds tells a story of inequitable consolidation. The UKRI institutes, being a state body, provide an opportunity for establishing innovation in areas where it is lacking. However, the reality is yet more concentration in already innovative areas—they cluster in the North Belt and The Golden Triangle. Universities, too, have a concentrated R&D system. As The Economist attests, “Nearly half of public r&d money ends up in the “Golden Triangle”, as Oxford, Cambridge, and London’s best universities are commonly known”. I illustrate the disparity below for 3167 grants totalled by amount per institution through councils. Then I illustrate the Research England inequity.
Funding is distributed to winners through a. competitive project proposals to individual councils b. Research England’s research excellence framework assessments weighted by “outputs (65 per cent), impact (20 per cent) and environment (15 per cent)”. C. Knowledge exchange collaboration and—not included above—research capital grants. (Innovate UK meanwhile has £1154M in 2021 to invest in facilitating businesses.) Precedent reigns for previously high performing R&D streams and institutions are likely to receive more funding and thereby perform better and thereby receive more funding.
The sociologist of science Robert K Merton identified and named this cumulative advantage the Matthew Effect specifically for science publishing and multiplier claims on intellectual property from previous intellectual property (IP). The effect remains pertinent to IP and in the cumulative advantages of compounded enterprise via network effects. For example, Cambridge city boasts the most patents per-person because public and private research and development and innovation coalesce and compound each others’ advances in a geographic public-private business network. Yet Cambridge University doesn’t boast many patents for its performance levels—the relationship of Research Park to University, judged by IP metrics, is parasitic. The 2021 Roadmap confirms enthusiasm for research intensity above research distribution:
UKRI, then, demonstrably hasn’t levelled up the rest of the UK to the R&D innovation standards of East England. The policy whereby “The highest-ranked research receives four times as much cash as the next best under the main funding stream” may appear meritocratic. But it precludes other institutions and other towns gaining a world-leading prominence. Despite rhetoric in UKRI and its Places Fund about the public good, levelling up the UK, and moonshot targets the reality on the ground looks far different. Indeed, The Financial Times cautions that the UK won’t even fulfill its national R&D budget-raise. The strategy towards Grand Challenges and equitable distribution is already questionable at the local, communities, level.
Critique and Classify: Rhetoric Versus Practice
The UK R&D Roadmap 2021 characterises innovation as “the process by which ideas are turned into economic growth – where discoveries are translated into new products, services and jobs, creating positive change in businesses, public services, government and wider society”. The roadmap is definitively pro-innovation since it defines innovation as only “positive change”, and assumes that change diffuses throughout “wider society” for the public good. Innovation, however, does have negative changes and often concentrates in narrower society. For example, Mazzucato explains that high-risk innovations have profited share beneficiaries more than public servants who have invented them. Regionally, too, those better off tend to get better off. Contrary to “levelling up” across the UK the strategy for places fund, is predicated on the idea of “building on strengths”, an approach which precludes new opportunities being explored in areas where innovation is needed to attract private enterprise. The move towards public-private hybridisation maintains a dogma that allocating funding for infrastructure and R&D, where there is little already, is inefficient and thereby an ‘impossible’ allocation. The Economist for example maintains that elitist concentration of R&D is behind UK university success in global rankings—and should keep at it—stipulating that Tories offer the rest of the UK R&D as a political token to merely sway voters. Albeit a view characteristic of contemporary innovation policy in the UK, it is a ruthlessly marketist view. Total growth is no advantage unless it is actually distributed across civil society; the wider society growth that innovation, remember, UKRI ostensibly serves. And innovation, moreover, depends on the networked exchange of public-private enterprise but the state can lead the way in making markets, not just in facilitating them. A public institution royalties system would allow for sufficient return directly to a national innovation fund, as Mariana Mazzucato recommends.
Presently, however, the onus in UKRI is on fostering businesses in partnership rather than commercialising publicly-funded output itself for direct return. Without discoveries legally claimed by public institutes, private partners are those who stand to benefit from the investment and work despite a lionshare performed by publicly funded researchers. The UKRI consolidation is a step in the right direction—allowing for more interconnections and streamlined communications is a good thing. But a concerted IP system fund would allow UK innovation policy to deliver on its challenges for the sustainable long-run. Presently UKRI policies still over-prioritise short term business in universities rather than making good business of universities; UK innovation policy has made a loss-leader of the state but not yet a benefactor entrepreneur. In conclusion, I have argued that innovation policy is in the process of being re-characterised as a joint venture of state-market enterprise. I argue that while this re-characterisation is overall a good move, the government’s grand challenge rhetoric promises more than it delivers in practice. My exploration of how the UKRI works, its objectives, policies, institutions, and funds, incentives and fund distribution showed a UK innovation policy converged on state-market innovation. Given the recent 30 years of the UK R&D portfolio this recharacterisation is a remarkable shift. Despite failures to level up the rest of the UK, fulfill much in moonshot goals, or make markets for public goods like equitable distribution, all of these now at least make the agenda. The incipient framing offered by Vince Cable, “where profit seeking entrepreneurs as well as an entrepreneurial state” prosper, has it the wrong way round; a prospering state makes markets for profit seeking entrepreneurs to emerge. UKRI policy is arguably unsustainable in valuing entrepreneurs and companies without valuing a sustainable statist innovation circle in turn. Whitehall wishes to make Britain an entrepreneurial state but so far has prioritised making it a facilitator for opportunistic entrepreneurs.
Geneticists, such as Adam Rutherford at University College London, occasionally claim that racism is false because genetic variance shows humans’ current preoccupation with melanin pigmentation, bone structure, and singular origin stories are but misapprehensions. The idea of ‘a race’ is a mistake since the appearance and character traits, social and bodily, within any population are changeable and incrementally changing all the time. Granted, it is good to hear there is no biological basis for judgements about race; the racist judgements nonetheless continue, albeit more subtly, for social reasons. (That at the level of learning can still be considered part-biological, because detecting and acting on differences happens in our bodies’.) Nonetheless race’s biological status has had fraught currency since 1778, when the first person to study skull sizes and coin still-used race terms like Caucasian – Johann Friedrich Blumenbach, with benevolent racism – claimed ‘the African negro’ individual to be as potentially capable as any member of the French Academy. Biologists at Unesco in 1950-51 released then-daring statements that there is no pure biological basis for race in the flurry of post-war rights movements and post-decoding the double helix.
And as far afield a group as literature undergraduates since the 1990s have had readings such as Kwane Anthony Appiah and Henry Louis Gates’ critical essayson race, which spread the good news that genetic research had long-disproved any genetic basis for separate races. So, why do geneticists like Adam Rutherford continue to ‘reveal’ to the public at large that race is no objective fact, but a social development? For good intentions: to counter argue racists. But for bad reasons: the assumption that biological facts have primacy basis in how people, such as miseducated racists, treat one another. Sociological facts instead, such as personality, skin colour, accent, educational attainment, class, gender, nationality, ethnicity, looks, age, tabulated race, folk-psychology, personal-experience, status, and customs all go into determining how people treat one another. Think about it. Few racists consult a textbook, their doctor, or Radio 4 for advice or justification about what makes a population they dislike ‘the way they are’; disinformation forums in social media and in the darkest depths of the dark web are more hospitable venues. And in staking aggressive claims as Rutherford does in racists being his enemy and the enemy of science, he is liable to entrench and encourage in-and-out group divisions rather than broach cooperation and conversion to anti-racism. Consider how Nelson Mandela brought change through forgiveness, understanding, and peacemaking rather than treating others as ‘enemies’, for instance, he learnt the language, Afrikaans, of his oppressors in order to reach out to them.
Most at stake with the premises of anti-racist geneticists arguing with racists by appeals to genetics, however, is that it implies that were genetic correllates found for race groups then sterotyping judgements would be legitimated as mostly correct, as an archetype. And presumably therefore ok. Such claims suggest that genetics has primacy over behavioural sciences and even ethics.
Well-meaning commentators themselves tend to lapse into conflating biology facts with the ethical tribulations of social darwinism, eugenics, racism, ethnicity and xenophobia as well. Let us take a usefully broad brush here, just to remind ourselves.
Social darwinism is the idea that social competition among people is the work of natural selection improving humanity.
specifically : a sociological theory that sociocultural advance is the product of intergroup conflict and competition and the socially elite classes (such as those possessing wealth and power) possess biological superiority in the struggle for existence
Eugenics is the idea that altering and selectively matching parents or their alleles can improve humanity.
With singular agreement. (The study of) the arrangement of human reproduction in order to increase the proportion of characteristics regarded as desirable (or to reduce the proportion regarded as undesirable) within a population or the species as a whole. Also: the advocacy for or implementation of policies and practices intended to influence human reproduction in this way.
Racism is the idea that people should be treated differently because of their skin colour traits.
Prejudice, antagonism, or discrimination by an individual, institution, or society, against a person or people on the basis of their nationality or (now usually) their membership of a particular racial or ethnic group, typically one that is a minority or marginalized
Ethnicity is the idea that a person belongs to and is part responsible for, and to, an extrafamilial kindred group they have associated with before.
Status in respect of membership of a group regarded as ultimately of common descent, or having a common national or cultural tradition; ethnic character.
Xenophobia is a prejudice against an out-group, them, or their customs for their being different to an in-group, us, or our customs.
Dislike of or prejudice towards people, cultures, and customs that are foreign, or perceived as foreign.
Granted, the concepts are fuzzy in our contemporary world; and there is a family resemblance between all of them. They are linked. Nonetheless, geneticists arguing with racists by appeal to DNA in this light becomes questionable. Especially since racism predates genetics, and social darwinism predates genetics as well. Hearing too little of the genetic science is not, therefore, what is to blame for insidious prejudice. And recourse to genetics rather than ethics bears implications.
Most worrying is the implication that were genetic correlates found for a population then – to follow the logic – the judgements would be correct, and thereby more reasonable. A reader may balk at that repeated suggestion: ‘eugenics is not genomics, old science is not science today’. You may say. But to think so diametrically of then-versus-now, fake-versus-real science, falls into what Dr Melanie Smallman, senior lecturer in Science and Technology Studies at UCL, calls the ‘science to the rescue’ phenomenon. (Full disclosure: Smallman has lectured me.) Whereby science equals always good, always warranted, always desirable. Even when it plays a hand in bad outcomes, more engineering, technology, and science are deemed exponentially required. And science, of course, is seldom blamed for, or accessory to, worse ethics. Indeed science is often used as an arbiter of ethics – per genome studies proving more variance inside groups than between them, proves race and by extrapolation racism to be ‘false’.
I refer to the corollary sensibility that science used to be bad but is now all good, as ‘the bad old days fallacy’, pertinent to old fashioned scientisim—the promotion of science as the best means to determine values and choices regardless of how wrong that approach has gone for what was called science in the past. Eugenics was an establishment science upheld by scientific luminaries. But even luminaries today use tools eugenicist scientists designed or refined. When you apply a scientific statistical tool like population, for instance, down to a family, a university cohort, or a single person’s genetic profile, judgments against and about people being correct have become accepted practice; and deemed a fact we should, somehow, submit to putting into further practice. For instance in matching career to genomic score or tailoring learning support or instituting rounds of psychometric tests ahead of a job interview. Despite the fact that sociology and environment contain the labs where discoveries in behavioural genetics are made and contingent tools like population analysis are applied—the environment and social debates have little epistemic prestige (and little funding money) by comparison to prestigious fields like genomics. Or even Machine Learning: Nature Communicationpublished a paper in April 2020 dubiously assessing trustworthiness displays in paintings, as having been raised with Gross Domestic Product (GDP), a hypothesis ‘scientifically’ labelling those from poorer nations – perhaps inadvertently – as less trustworthy, on meager evidence.
Or consider the case of Robert Plomin. A behavioural geneticist, at King’s College London. Plomin advocates that selective schools select students’ DNA within the successful students. And this is no off-hand remark: Plomin claims that in his book Blueprint (Penguin, 2017) and on platform at Google Talks. He goes so far as to say that the school attended makes negligible differences to life path; parents should not bother to seek out better schools and Ofsted – the UK school review organisation – should rethink its budgetary priorities about making schools achieve higher standards. Because some genomic scores are just better for attaining grades and desirable intelligence quotient (IQ) scores than others.
Genomic scores determine as much as fifty and seventy per cent of the slices in the pie charts of IQ and educational attainment respectively. And the other social factors Plomin concludes are too random and too messy to address in any systematic way. Professor Plomin happily reveals his own academic achievement polygenic score to be “in the ninety-fourth percentile”. He also advocates that everyone should similarly learn to “grow into their genes” and consult their DNA profile to inform suitability for their path in life. Meanwhile, figureheads with much heated press sometimes openly celebrate the same fact infused sentiments. Boris Johnson, in a taped 2013 speech, declared that IQ differences between (“16 per cent below 90, 2 per cent above 160”) people determines who comes out-on-top and down-at-bottom in hierarchy—just as, in his bizarre analogy, “a well shaken cornflakes packet determines that some rise inevitably to the top”. (Maybe, a mistaken analogy to the Galton board? A device which demonstrates ‘normal’ distribution in balls running down a studded board.)
Boris Johnson’s adviser Andrew Sabisky was fired in February 2020 for his eugenic sentiments; he advocated forced sterilisation and selective births. Sabisky was first endorsed by Dominic Cummings, who on his blog flirts with the idea that the NHS should pay for intelligently designed babies. Babies better able to serve the state in world competition. And clinical psychologist Jordan Peterson of Toronto University—who boasts 137 published papers—lectures with power-point slides ranking profession by IQ (and referencing scores) implores his audience to align their aims to their cognitive limitations. That audience is no paltry lecture room but 2,837,424 views on Youtube. Noteworthy is that these figureheads are themselves winners in this apparently genetic IQ lottery and hierarchy; a fact feminist theorists like Helen Logino opine as mistaken personal epistemy. Their lack of experience at the bottom likely renders them complacent about naturalising inequities. These eclectic characters, moreover, are not an eccentric fringe within The Establishment. Robert Plomin, for example, counts among the most cited psychologists in the world, and his genetics research bears implications for life and death decisions.
In 2017 disability rights advocate Frank Stephens testified to the US Congress against proposals to cede National Institutes of Health (NIH) funding away from Downs Syndrome research; the proposals to cede funding were predicated on trends for fewer Downs Syndrome births making it past genetic screening, (nevermind the celebrated utility of would-be CRISPR Cas-9 gene-edits in future). Stephens even felt the compunction to appeal to the economic and scientific ‘justification’ for Downs Syndrome funding: Downs Syndrome is a useful case study for the investigation of Alzhimers; rather than those with Downs Syndrome having a right to life as a given.
Therefore the assumption that genetics has wholesale moved on from the bad old days is mistaken. However nice its geneticist practitioners and however nice its health uses, technology and science feed into politics, and politics feeds into technology and science – in worse ways as well as better ways. For leftist or rightist aims. Most horribly pertinent is China’s 1988 Gansu province law which ended with 5000 sterilised citizens who recorded IQ scores below 90. And in 2021 Uighur citizens are being forcibly sterilised – so reports The New York Times – in a concerted attempt to use eugenics to oppress race, ethnicity, and religion; Han men are encouraged to absorb the different populations of Xinjiang women—and Xinjiang women are rewarded for ethnically and racially ‘correct’ choices of husband with a car or a flat. (I say Xinjiang women because there are many oppressed minorities there, not just Uighur.) Scholars who know about eugenics recognise these as two cases of eugenic approaches, ones previously used in the USA: one is called ‘negative eugenics’ which refers to preventing the procreation of undesirables and the other ‘positive eugenics’ which refers to encouraging the procreation of desirables. As late as 2010 imprisoned Californian women were forcibly sterilised – an example of negative eugenics. As recently as 2021 fewer disabled Britons were permitted resuscitation – another example of negative eugenics, albeit tacit.
Eugenics therefore happens in some of the most influential countries like China, the USA, and UK, in the 21st century.
In the more banal scientific industry, too, misuse of genetics reigns amid the most noble of aims and fanciest of research projects. The BRAC-1 and BRAC-2 genes which predict bad case breast cancer were patented by a genetics company, Myriad, in 2001 thanks to hardworking geneticists in its labs. It took the US Supreme Court to overrule its patent in 2013 which, before then, accrued extortionate amounts of money in ownership fees for health insurance companies to test whether someone had the undesirable genes. Without regard to whether that precluded treatment for poorer persons’ with BRCA 1 or 2 variants. Even the justification The Supreme Court gave was based on the implausibility of patenting a ‘natural’ gene which leaves open to interpretation and debate the future of synthesised and CRISPR-CAS 9 modified genes. Especially given the dynamics of different nations embracing cutting-edge tech competitively; who knows what the future of artificial genes holds. What begins in moral repairs, may slide to dubious upgrades. In the future people with my ASD disorder profile may be prevented from birth; the line between pathology and health, such as in a spectrum disorder, is far from clear-cut. The creators of CRISPR-CAS-9 themselves worry about what traits their ‘genetic scissors’ might cut out of the future.
Instead of lamenting the misuse and abuse of science as behind us, we should look to the past and the very real present of eugenics within genetics today, to best guide us. Genetics technologies will be used for worse, neo-eugenics, and better, social fairness, aims depending on how we regulate tech, patents, and ideas now—democratically. Initial conditions have an outsize impact later; ignoring the issue as most of the news cycle does is no solution and merely allows its flourishment. We may repeat the same mistakes as our shamed forebears. From the viewpoint of Frank Stephens, the anonymous Uighur victims, the disabled patients who were accorded non-resuscitation status more than able Britons, Americans sterillised by California in 2010, we already are practising eugenics. To overlook these examples as somehow beyond science, devices, and circulated authoritative ideas (such as genome-centred arguments racism is a science error rather than a values problem) is to ignore, in Stephens’ words, “the canary in the eugenics coal mine”.
In the midnight hour of the 26 September 1983, a warning algorithm alerted Stansiav Petrov that five missiles were bound for Russia. Petrov alerted his officers at the Kremlin and a salvo of five missiles was sent out to New York, Los Angeles, Washington DC, San Francisco, and Seattle. That is how the nuclear war began in the 1980s. Of course this is an alternative history. Here is what really happened: Petrov chose to wait and see. After 23 minutes, no missiles arrived. The nuclear war initiated by a cutting-edge algorithm’s error never happened thanks to Stansiav Petrov’s intuition. He recounted that five missiles is an illogical number to send if you wish to destroy your enemy; it had to be computer error.
The parable of this story is that human discretion in the use of dangerous technology is important. If the missiles and response algorithms had been automated back then, nuclear war would have broken out. Fast-forward forty-nine years later however and the USA, Russia, China, and the UK are making ultra-advanced weapons which act and respond of their own accord. Their name among the public, who do not work on or with them, is ‘killer robots’. The name unfortunately invites images of terminators and science fiction stories (often in the banner of news stories). Such a name nevertheless belittles the real-world threat these devices—lethal autonomous weapons—pose to the world.
The STM Kargu drone, for example, has the capability to home in on targets and shoot them dead without piloted guidance. Think a tiny robot, with guns, that is able to target, fly, and shoot without direction from its masters. Confirming the worries of activists such as Stuart Russell (Professor at Berkeley) and Noel Sharkey (Professor at Sheffield University) who are experts in artificial intelligence and its robotic application, a United Nations report concluded that a Kargu killed a man in Libya, despite the drone having no instruction to pursue him.
Turkish made Kargu Rotary Wing Autonomous Attack Drone Credit: STM
This report is no surprise to researchers in science and technology. The Kargu website advertises its capability, such as its autonomous “guided elimination modes against targets selected on images or coordinates”, on its website. And if autonomous weapons are deployed in warfare, then those weapons will assuredly kill people autonomously. More nightmarishly, Kargu has a self-destruct function, so resistance fighters can never turn the weapons against their masters. The implications for authoritarian states who wish to keep the people in line, through technological means, is chilling.
Houthi rebels nevertheless pre-programmed 18 bomb carrying drones and seven cruise missiles which struck Saudi Arabian oil fields in September 2019. The result halved oil output, inflating world oil prices. And the most worrying part is that these drones were piloted through GPS—and made it past a richly endowed defence system. The capability of weapons that are autonomous is astoundingly frightening, therefore, given what non-state actors, often terrorists, can already do co-opting already existent technologies like drones. Imagine autonomous drones in the hands of civil war and freedom fighters!
Stuart Russell, who advises the UN, laments that non-state actors, terrorists, using autonomous weapons like Kargu drones are practically “inevitable” as the weapons become cheaper and common-place through market competition for lower prices. Turkey has bought 500 of these Kargu drones; these drones fly in the Libyan skies and were behind the automated-murder of the annonymous rebel featured in the United Nations’ report.
Mark Esper, US Defence Secretary, asserted at a conference in November 2019 that “the Chinese government is already exporting some of its most advanced military aerial drones to the Middle East, as it prepares to export its next-generation stealth UAVs when those come online”. The lethal autonomous weapons developments just keep coming. I will tell you about some of them.
The US Navy has an X-47B unmanned fighter jet which can refuel mid-air, land, and take off without a pilot. The Chinese military has a ‘Dark Sword’ jet which maneuvers in patterns humans could never tolerate; with no brain cargo to suffer g-force side-effects ‘Dark Sword’ has more capability than any human piloted plane ever has had. Russia meanwhile is automating its cutting edge T-14 Armata tank, and Kalashnikov, a Russian tech company, has created automated combat modules for enhancing artillery guns and tanks to perceive, select, and fire on targets autonomously.
The Dark Sword Fighter Jet, Credit: Nationalinterst.org
The competition between different nations amounts to an arms race. Each country looks to develop weapons able to overwhelm and neutralise others’ which means constant redevelopment and reinvestment in outcompeting the others in capability. Countries with disadvantages in military can make up the differences, in soldier numbers or air superiority, with disruptive levelling technologies. Defence spending is on the increase into these advanced killing machines. And a big investment is in drone swarms fully equipped with both pilot and kill functions, working together with machine learning algorithms to identify weaknesses in enemies’ defences to eliminate them as efficiently as possible. Such technological development inspired Professor Russell. He presented to the United Nations a satire video of their hypothetical use, including a mock Ted-style presentation with tragic reporting.
Despite such illustrations coming true, the United Nations struggles even to set parameters for even the ‘ethical’ use of these weapons. As Ozlem Ulgen, international lawyer, ethicist, and adviser to the UN outlines, the creation of these weapons can be argued to be illegal in Humanitarian Law because the machines cannot discern a surrender scenario or be sure to target correctly. Soldiers in international law must react appropriately to those who surrender by taking them prisoner, giving medical assistance to the injured, and so on.
Nonetheless the law in word and the law in practice are different. Soldiers sometimes forgo following those rules, and likewise without more explicit wording against lethal autonomous weapons in legislation, countries such as China and Turkey forgo ethical issues and feel free to flaunt their weapons’ capabilities. The Russian ambassador to the UN, according to Stuart Russell, also claims the weapons don’t exist yet so nothing needs to be done. The British Home Office is also against a ban, telling The Guardianin 2015 that “At present, we do not see the need for a prohibition on the use of LAWS [lethal autonomous weapons systems], as international humanitarian law already provides sufficient regulation for this area.” The temerity in the claim is in friction with Ozlem Ulgen’s claims, and the consensus within the roboticist community.
Now, some commentators claim, however, that introducing lethal autonomous weapons to the battlefield would be a good thing, because they could replace real soldiers on the ground who are themselves imperfect. This idea is broached by Melanie Phillips, The Times commentator,on the UK BBC 4 Podcast The Moral Maze who suggests robots fighting robots is a better state of affairs. But that is nonsense. Real war in Syria, Lybia, and terrorism in Sub-Saharan Africa shows robots targeting humans. Ronald Arkin, a roboticist, concurs with Philips that autonomous weapons are more accurate and less likely to go haywire than are humans, however, the potentiality for use is far too unpredictable for him to safely make such claims about the relative safety of a technology that is incomparable to scale a reasonable comparison, at least to scale in favour of autonomous weapons.
Because the flaw in Lethal Autonomous Weapons (LAW) systems is actually that they are too efficient and will execute their commands and victims alike without a conscience and zero intuition towards rebellion or reasonable grounds for treason.
Those in the know, such as roboticist Noel Sharkey and artificial-intelligence professor Stuart Russell want Lethal Autonomous Weapons (LAW) banned. LAW are in Stuart Russell’s words “weapons of mass destruction”. At CogX, an AI festival, in 2020 Russell said a “vanful of lethal autonomous weapons are capable of causing more deaths than nuclear weapons” and at “a cheaper price”. Yet there has been seemingly little public uproar about these killing machines. I for one have petitioned the commons and lobbied my MP; everyone should.
Campaigns like Stop Killer Robots are supported by those worried in academia and industry such as the late Stephen Hawking. An open-letter signed along with 4502 other AI and robotics researchers, 26215 concerned signatories pleaded for firmer regulations on the weapons. It’s remarkable that people most in the know about the technology are at the forefront of regulating it. Given how enthused technologists are about their innovation and their implications it is a red flag that so many wish to close down their development who are closest to developing the application of algorithms elsewhere.
Just as physicists worked to mitigate nuclear weapons (Geneva Prohibition on Nuclear Weapons, 2017), biologists to ban biowarfare (Biological Weapons Convention, 1972), and chemists to ban poison gas weapons (Geneva Protocol 1925), AI and robotics experts are advocating more action than politicians are currently acting on and the public lobbying for.
The risked lives from these weapons are too great for citizens to leave in the hands of government officials and military contractors alone. The lethal autonomous weapons are not merely weapons leveraged with robot against robot but competing networked algorithms working in chaotic coordination. Because ‘friendly’-algorithms would be competing against ‘enemy’-algorithms and learning against each other the risks for escalation are too great.
Video demo from Military Technology debating WMD status
The algorithms are too complex for humans to understand; many programmers are writing programs they themselves cannot read. But how algorithms come to conclusions being obscured is not the only danger – speed is the most worrying. Humans are incapable of processing at the speeds autonomous weapon swarms would operate at.
Therefore a narrative as expounded by the British Home Office claiming regulations already cover lethal autonomous weapons—with humans retaining control—is definitively weak. As Peter Lee, computer scientist and ethicist at Birmingham City University claims, “artificial intelligence is definitely a great tool if we want to help a human but again and again we see it’s a very poor tool when trying to replace a human”.
The discretion Stlansilav Petrov exerted in ignoring the algorithm which mistakenly alerted a nonexistent missile strike would be absent in an autonomous weapons scenario. Given that Russell claims these weapons will cause more damage than nuclear weapons, the implications of their unchecked proliferation are grave. A narrative on risk reduction and managing such devices is therefore arguably misplaced. Without the presence of a hazard, there is no risk to manage. Without lethal autonomous weapons there would be no weapon to use, regulate and re-negotiate, for different battlefields—or terrorist opportunity. The real discretion comes collectively, now, by campaigning to ban these weapons before they get out of hand. For Libyan victims of Turkey’s Kargu drones, lethal autonomous weapons already have.
This question arguably bears an assumption: that reading philosophy classics has been useful to science before, whereas now reading them for use is dubious. Granted, many first-rate physicists dismiss philosophy. An assumption that philosophy has no value to offer ‘actual’ science today is common. Stephen Hawking said, “Philosophy is dead”. And Richard Feynman and Lawrence Krauss agree. Research funding favours technology over thinking; armchair speculation is literally less valued. The success of science, however, owes a debt to armchair speculation: natural philosophy became a victim of its own success; its philosophical positions a minority practice. Philosophy is about debate. Authorities, like above, do not have the final word. And anyway, heavy-weight authorities like Albert Einstein entertained philosophies in their discoveries. Quantum physicist David Deutsch is even a Popperian. The answer to whether it ‘makes sense’ to read these classics is yes, and no. (Besides, in a liberal country people decide for themselves.) Arguably reading classics rewards A. in methodological dialogue with contemporary scientists B. in solving scientific puzzles and C. in ordering science policy and practice.
The axioms of science come from philosophy. Scientists like Hawking are akin to the monsieur in Molière, who never knew he spoke in prose. Scientific method and testing is close to heart, and one prototype comes from philosopher Francis Bacon. Without even reading Bayes, Bacon, J.S.M, Popper, Kuhn, or Lakatos scientists follow many of their prescriptions. The sign of their success is their being taken for granted. In that sense, no it does not make sense to read the classics. Reading the classics is as irrelevant as reading the constitution – so long as it is followed it works. Kuhn reasons similarly for a paradigm is the bed of assumptions scientists work locally within, seldom to upend. New paradigms like new constitutions are rare. Yet to know what – how and why – one is doing, yes, reading science philosophy classics helps. The supposed ‘replication crisis’, for instance, rests on assumptions which begrudge an ir-replication rate as somehow aberrant to science, when in fact they match Popper’s falsification criterion. The replication assumptions, too, ignore how Liptonian triangulation makes more reliable causal inference. Multiple effects, require multiple causes and methods to reliably explain them. Yet ‘tests’ for causes underplay effects beyond the procedure. Studies, for example, that identify moderate drinking is positively correlated with healthy people, ignore the very long-term effects on life expectancy and the confounder that already ill people are forced to quit drinking. Meanwhile, in A.I research hard-nosed scientists who cherish replication and evidence-based practice, speculate ‘superintelligence’ and ‘The Singularity’. A dose of Popper would tame the contradiction between belief in research from plain facts and their practised speculation and thought-experiments.
Whereas Kuhn would support their speculation: an A.I ‘revolution’ leads normal science into a new worldview not from deducting objective facts alone but inducting fashionable theories across scientific communities; to excoriate, new, anomalies. A revolution comes from scientists who have imagination, biases and tastes. Feyerabend, too, can illuminate A.I research. He says the powerful scientists inflate their roles and accrue power for themselves rather than to the special end of betterment or elusive truths. He says one could substitute “normal science” with “organised crime” and its demarcation remain. Too provocative, but A.I researchers indeed do research in their interest. Programmers seldom choose no-programming for a solution nor admit irrationality. Which is problematic given that humanity, as a whole, is techspeak illiterate and code innumerate—inequality is inbuilt with artificial intelligence today. (Virginia Eubank’s book Automating Inequality documents this well.) Scientists are self-interested and humanly irrational more than is presumed, performed, or admitted.
Helen Longino stresses how values permeate science. Contrary to a paternal narrative of previous philosophers’ objectivity claims, she offers contextual empiricism. Which comfortably counts thinking and evaluation within science; marginalised ethnicities and women within science; and how science emerges from communities with gender, race, class, (and ableist, she herself misses in these texts) disparities rather than follow any Great Man narrative. Longino works ‘with’ Kuhn to create criteria, upgraded for today. Late-Kuhn suggests science ought to be accurate, consistent, general in scope, and be progressive in solving problems: “disclose new phenomena or previously unnoted relationships among those already known”. Longinio stresses “shared standards” in lieu of vague ‘consistent’ and “uptake of criticism” to stress gradualist worldview change rather than dramatic and rare ‘revolution’. Key however is that social context precedes scientists and guidelines. Hence a contextual empirical science with feminist principles, with value ladenness and intellectual equality, does “not just make philosophical sense of the notions of feminist and/or oppositional science, but that also deepens our understanding of mainstream science.”
Without equal intellectual authority, science goes (ethically, unusefully) awry. Scientific puzzles puzzle more. Without women psychologists stress responses would be misunderstood; without women neuroscientists, neurological differences would be read in sexist ways. Indeed, both are male-biased and sexist still. But without women scientists, it would be more so. According to some women researchers ‘fight or flight’ is skewed toward males’ behaviour. Brain differences are fabricated for sexist motives. Without the enforced criteria of Longino, such anomalies would be vacant from our scientific map. Other potent arguments hold for LGBTQ+ and diverse ethnicities among genetic researchers—pseudoscience for bad ends becomes harder.
Note Longino does not bin Kuhnian texts but deftly incorporates social context and values into contemporary guidelines and procedure. That a persons’ worldview is acknowledged as paradigm relative actually enables better communication, or ‘translation’, between paradigms. Science is more productive in a dialogue rather than in what Feyerabend calls the tyrannous “rule of rationality”. True, authority from expertise does always have an important role. Longino could go further, though. The generosity granted to ‘contexts’ does not figure nonindustrial societies or art within her scheme. Longino claims “the equality of intellectual authority” and “diffusion of power” but it remains fixedly within institutional and discipline borders—in a world where knowledge abounds regardless of profession.
Reading these philosophers of science helps to decide what counts. Even if a proposition is axiomatic—and STEM has axiomatic prestiges, its funding never ending—it is essential to question it lest people forget what justifies their beliefs. Debates and problems in science become easier with classics at hand; if not to agree with, then to know what you disagree with. Reading classics benefits in contemporary dialogue (like Deutsch, and A.I); in honing scientific puzzles (like neuroanatomy, and stress); in ordering policy and practice (like prejudice, and pseudoscience). Especially when and where scientific future-futures are taken for granted to be better, progressive and always profitable.
