Contra Corey Pein, Computer Science Is A Science

In this day and age, sophisticated critique of technology and science is much needed. What we don’t need is critiques like this long piece in the Baffler by Corey Pein which, I think, is trying to mount a critique of the lack of ethics education in computer science curricula but seems most concerned with asserting that computer science is not a science. By, I think, relying on the premise that “Silicon Valley activity and propaganda” = “computer science.” I fail to understand how a humanistic point is made by asserting the ‘unscientific’ nature of a purported science, but your mileage may vary. Anyway, on to Pein.

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Neil deGrasse Tyson And The Perils Of Facile Reductionism

You know the shtick by now–or at least, twitterers and tweeters do. Every few weeks, Neil deGrasse Tyson, one of America’s most popular public ‘scientific’ intellectuals, decides that it is time to describe some social construct in scientific language to show how ‘arbitrary’ and ‘made-up’ it all is–compared to the sheer factitude, the amazing reality-grounded non-arbitrariness of scientific knowledge. Consider for instance, this latest gem, now predictably provoking ridicule from those who found its issuance predictable and tired:

Not that anybody’s asked, but New Years Day on the Gregorian Calendar is a cosmically arbitrary event, carrying no Astronomical significance at all.

A week earlier, Tyson had tweeted:


Tyson, I think, imagines that he is bringing science to the masses; that he is dispelling the ignorance cast by the veil of imprecise, arbitrary, subjective language that ‘ordinary folk’ use by directing their attention to scientific language, which when used, shows how ridiculous those ‘ordinary folk’ affectations are. Your birthday? Just a date. That date? A ‘cosmically arbitrary event.’ Your child’s laughter? Just sound waves colliding with your eardrum. That friendly smile beamed at you by your school mate? Just facial muscles being stretched. And so on. It’s really easy; almost mechanical. I could, if I wanted, set up a bot-run Neil deGrasse Tyson Parody account on Twitter, and just issue these every once in a while. Easy pickings.

Does Tyson imagine that he is engaging in some form ‘scientific communication’ here, bringing science to the masses? Does he imagined he is introducing greater precision and fidelity to truth in our everyday conversation and discourse, cleaning up the degraded Augean stables of internet chatter? He might think so, but what Tyson is actually engaged in is displaying the perils of facile reductionism and the scientism it invariably accompanies and embellishes; anything can be redescribed in scientific language but that does not mean such redescription is necessary or desirable or even moderately useful. All too often such redescription results in not talking about the ‘same thing’ any more. (All that great literature? Just ink on paper! You know, a chemical pigment on a piece of treated wood pulp.)

There are many ways of talking about the world; science is one of them. Science lets us do many things; other ways of talking about the world let us other do things. Scientific language is a tool; it lets us solve some problems really well; other languages–like those of poetry, psychology, literature, legal theory–help us solve others. The views they introduce of this world show us many things; different objects appear in different views depending on the language adopted. As a result, we are ‘multi-scopic’ creatures; at any time, we entertain multiple perspectives on this world and work with them, shifting between each as my wants and needs require. To figure out what clothes to wear today, I consulted the resources of meteorology; in order to get a fellow human being to come to my aid, I used elementary folk psychology, not neuroscience; to crack a joke and break the ice with co-workers, I relied on humor which deployed imaginary entities. Different tasks; different languages; different tools; it is the basis of the pragmatic attitude, which underwrites the science that Tyson claims to revere.

Tyson has famously dissed philosophy of science and just philosophy in general; his tweeting shows that he would greatly benefit from a philosophy class or two himself.

Contra Cathy O’Neil, The ‘Ivory Tower’ Does Not ‘Ignore Tech’

In ‘Ivory Tower Cannot Keep On Ignoring TechCathy O’Neil writes:

We need academia to step up to fill in the gaps in our collective understanding about the new role of technology in shaping our lives. We need robust research on hiring algorithms that seem to filter out peoplewith mental health disorders…we need research to ensure that the same mistakes aren’t made again and again. It’s absolutely within the abilities of academic research to study such examples and to push against the most obvious statistical, ethical or constitutional failures and dedicate serious intellectual energy to finding solutions. And whereas professional technologists working at private companies are not in a position to critique their own work, academics theoretically enjoy much more freedom of inquiry.

There is essentially no distinct field of academic study that takes seriously the responsibility of understanding and critiquing the role of technology — and specifically, the algorithms that are responsible for so many decisions — in our lives. That’s not surprising. Which academic department is going to give up a valuable tenure line to devote to this, given how much academic departments fight over resources already?

O’Neil’s piece is an unfortunate continuation of a trend to continue to castigate academia for its lack of social responsibility, all the while ignoring the work academics do in precisely those domains where their absence is supposedly felt.

In her Op-Ed, O’Neil ignores science and technology studies, a field of study that “takes seriously the responsibility of understanding and critiquing the role of technology,” and many of whose members are engaged in precisely the kind of studies she thinks should be undertaken at this moment in the history of technology. Moreover, there are fields of academic studies such as philosophy of science, philosophy of technology, and the sociology of knowledge, all of which take very seriously the task of examining and critiquing the conceptual foundations of science and technology; such inquiries are not elucidatory, they are very often critical and skeptical. Such disciplines then, produce work that makes both descriptive and prescriptive claims about the practice of science, and the social, political, and ethical values that underwrite what may seem like purely ‘technical’ decisions pertaining to design and implementation. The humanities are not alone in this regard, most computer science departments now require a class in ‘Computer Ethics’ as part of the requirements for their major (indeed, I designed one such class here at Brooklyn College, and taught it for a few semesters.) And of course, legal academics have, in recent years started to pay attention to these fields and incorporated them in their writings on ‘algorithmic decision making,’ ‘algorithmic control’ and so on. (The work of Frank Pasquale and Danielle Citron is notable in this regard.) If O’Neil is interested, she could dig deeper into the philosophical canon and read works by critical theorists like Herbert Marcuse and Max Horkheimer who mounted rigorous critiques of scientism, reductionism, and positivism in their works. Lastly, O’Neil could read my co-authored work Decoding Liberation: The Promise of Free and Open Source Software, a central claim of which is that transparency, not opacity, should be the guiding principle for software design and deployment. I’d be happy to send her a copy if she so desires.

Richard Dawkins’ Inconsistent Reliance On Pragmatism






Epistemology and ‘The Leftovers’







Pigliucci And Shaw On The Allegedly Useful Reduction

Massimo Pigliucci critiques the uncritical reductionism that the conflation of philosophy and science brings in its wake, using as a jumping-off point, Tamsin Shaw’s essay in the New York Review of Books, which addresses psychologists’ claims “that human beings are not rational, but rather rationalizing, and that one of the things we rationalize most about is ethics.” Pigliucci notes that Shaw‘s targets “Jonathan Haidt, Steven Pinker, Paul Bloom, Joshua Greene and a number of others….make the same kind of fundamental mistake [a category mistake], regardless of the quality of their empirical research.”

Pigliucci highlights Shaw’s critique of Joshua Greene’s claims that “neuroscientific data can test ethical theories, concluding that there is empirical evidence for utilitarianism.” Shaw had noted that:

Greene interpreted these results in the light of an unverifiable and unfalsifiable story about evolutionary psychology … Greene inferred … that the slower mechanisms we see in the brain are a later development and are superior because morality is properly concerned with impersonal values … [But] the claim here is that personal factors are morally irrelevant, so the neural and psychological processes that track such factors in each person cannot be relied on to support moral propositions or guide moral decisions. Greene’s controversial philosophical claim is simply presupposed; it is in no way motivated by the findings of science. An understanding of the neural correlates of reasoning can tell us nothing about whether the outcome of this reasoning is justified.

At this point Pigliucci intervenes:

Let me interject here with my favorite analogy to explain why exactly Greene’s reasoning doesn’t hold up: mathematics. Imagine we subjected a number of individuals to fMRI scanning of their brain activity while they are in the process of tackling mathematical problems. I am positive that we would conclude the following…

There are certain areas, and not others, of the brain that lit up when a person is engaged with a mathematical problem.

There is probably variation in the human population for the level of activity, and possibly even the size or micro-anatomy, of these areas.

There is some sort of evolutionary psychological story that can be told for why the ability to carry out simple mathematical or abstract reasoning may have been adaptive in the Pleistocene (though it would be much harder to come up with a similar story that justifies the ability of some people to understand advanced math, or to solve Fermat’s Last Theorem).

But none of the above will tell us anything at all about whether the subjects in the experiment got the math right. Only a mathematician — not a neuroscientist, not an evolutionary psychologist — can tell us that.

Correct. Now imagine an ambitious neuroscientist who claims his science has really, really advanced, and indeed, imaging technology has improved so much that Pigliucci’s first premise above should be changed to:

There are certain areas, and not others, of the brain that lit up when a person is working out the correct solution to a particular mathematical problem.

So, contra Pigliucci’s claim above, neuroscience will tell us a great deal about whether the subjects in the experiment got the math right. Our funky imaging science and technology makes that possible now. At this stage, the triumphant reductionist says, “We’ve reduced the doing of mathematics to doing neuroscience; when you think you are doing mathematics, all that is happening is that a bunch of neurons are firing in the following patterns and particular parts of your brain are lighting up. We can now tell a evolutionary psychology story about why the ability to reason correctly may have been adaptive.”

But we may ask: Should the presence of such technology mean we should stop doing mathematics? Have we learned, as a result of such imaging studies, how to do mathematics correctly? We know that when our brains are in particular states, they can be interpreted as doing mathematical problems–‘this activity means you are doing a math problem in this fashion.’ A mathematician looks at proofs; a neuroscientist would look at the corresponding brain scans. We know when one corresponds to another. This is perhaps useful for comparing math-brain-states with poetry-brain-states but it won’t tell us how to write poetry or proofs for theorems. It does not tell us how humans would produce those proofs (or those brain states in their brains.) If a perverse neuroscientist were to suggest that the right way to do maths now would be to aim to put your brain into the states suggested by the imaging machines, we would note we already have a perfectly good of learning how to do good mathematics: learning from masters’ techniques, as found in books, journals, and notebooks.

In short, the reduction of a human activity–math–to its corresponding brain activity achieves precisely nothing when it comes to the doing of the activity. It aids our understanding of that activity in some regards–as in, how does its corresponding brain activity compare to other corresponding brain activities for other actions–and not in others. Some aspects of this reduction will strike us as perfectly pointless, given the antecedent accomplishments of mathematics and mathematicians.

Not all possible reduction is desirable or meaningful.








As Robin says:



As Robin goes on to note:




Linker then moves on Purdy, summarizing his claims as follows:





Linker now fulminates:




And then, Linker levels that old canard:


