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Computer world

Justin E. H. Smith delivers a startling diagnosis for the humanities: they are not dying because of culture wars or critical theory, but because machines have simply become better at producing the "research results" that universities demand. In an era where artificial intelligence is reshaping epistemology, Smith argues that the current panic over academic integrity misses the forest for the trees, suggesting instead that we are witnessing a fundamental shift in how reality itself is conceptualized—from physical particles to information bits.

The Usurpation of Physics

Smith begins by dismantling the popular "simulation argument" often championed by tech figures. He contends that the idea that reality is more "bit-like than it-like" is not a profound new discovery, but rather the inevitable cultural echo of physics losing its status as the supreme science. "Perhaps the greatest propaganda coup of scientific modernity has been to convince a good number of us that such a claim is nothing more than right common sense," Smith writes, noting how quickly we accept that atoms anchor reality while dismissing hesitation as superstition.

Computer world

The author points to the 2024 Nobel Prize in Physics, awarded to computer scientists Geoffrey Hinton and John Hopfield for work on artificial neural networks, as a definitive marker of this transition. This event signaled that the highest distinction in physics can now be earned by decoupling from the "real" world of particles. Smith observes that we are transitioning out of a 400-year reign of physics as Prima Scientia, with information science taking the throne.

This historical framing is bolstered by a reference to ancient traditions that predate our current materialist obsession. Smith notes that classical Indian schools, such as those influenced by the grammarian Pāṇini around 400 BCE, took śabda or "speech" as the first principle of reality. Just as Pāṇini viewed linguistic particles as the constituents of the world, modern simulationists view digital bits. Smith argues that the naivety lies not in questioning materialism, but in assuming our new technologies are uniquely revealing the nature of the universe.

"It would be surprising indeed if the technologies that did so much to shape the adolescent minds of Musk, Bostrom, Chalmers... just happened also to be the clavis for unlocking the nature of the universe."

Smith draws a parallel to the 17th century, where the clockwork was the dominant metaphor for the cosmos. He suggests that declaring the universe a "clockwork" allowed natural philosophers to pursue "maker's knowledge," transforming nature into an instrument for human ends. Today, the computer has simply replaced the clock as the more impressive instrument. The claim "The cosmos is a computer" is true not because we have finally found objective truth, but because it licenses investigation in information-theoretical terms that yield remarkable practical results.

The Death of the Author and the Rise of Remainder Humanism

Turning to the immediate crisis in academia, Smith critiques a recent report by scholars like Paul Boghossian regarding the state of humanities scholarship. He argues that these critics fail to see that the primary threat to humanistic inquiry is not ideological bias, but the economic reality of machine-generated research. The core problem is that institutions still demand "positive research results," a metric that machines can now deliver far more efficiently than humans.

Smith warns that as long as humanities scholars conceive their work as "STEM lite" production of data, they are doomed to practice what Leif Weatherby calls "remainder humanism." He paints a stark picture for the future academic: "You can still get your Ph.D. on Kafka or Lucretius... but already you must prepare yourself for a life strung along on postdocs that are—if you're lucky!—only distally related to Kafka or Lucretius, while your actual work-tasks in fact look more like low-end data-entry."

The author suggests that the "critical humanists" have inadvertently aided this shift by adopting approaches that deny the primacy of scientific rigor, yet he insists the machine-dominated regime would have arrived regardless of their actions. The report Smith critiques is dismissed as a "power-move" that treats social media squabbles as the root cause of academic decline, ignoring the deeper technological displacement.

"Either way... you got the death of the author, and the death of the author precisely in his devourment by the machines his work served to train."

Critics might argue that Smith underestimates the unique value of human interpretation and ethical reasoning, which cannot be reduced to data entry or algorithmic output. However, Smith's point is not that AI can replicate human thought perfectly, but that the institutional incentives of modern academia are already aligned with machine efficiency rather than human cultivation.

Smith concludes that the report's proposed solution—a return to a naive theory of objective truth—is insufficient. The true defense for the humanities must lie elsewhere, in areas machines cannot easily penetrate: "ethical self-cultivation, or civic belonging, or discovery of meaning in tradition." These are the only anchors left when the production of positive results is no longer the exclusive domain of human scholars.

Bottom Line

Smith's most compelling insight is that the crisis in the humanities is not a failure of ideas, but a collapse of function; if machines can do the "research," the justification for the profession must shift from data production to meaning-making. The argument's vulnerability lies in its potential fatalism, assuming that institutions will inevitably prioritize machine efficiency over humanistic depth without significant resistance. Readers should watch for how universities adapt their funding and tenure models as AI tools become indistinguishable from traditional research output.

Deep Dives

Explore these related deep dives:

  • The Grammar of Science Amazon · Better World Books by Karl Pearson

  • John Archibald Wheeler

    This John Archibald Wheeler concept provides the specific philosophical origin for the article's critique of simulationism, explaining how the metaphor that reality is fundamentally 'bit-like' rather than 'it-like' was coined to bridge quantum physics and information theory.

  • Nobel Prize in Physics

    While the article mentions the winners, this entry details the unprecedented nature of awarding physics honors for machine learning algorithms, serving as the concrete evidence for the author's claim that 'information science' is usurping physics as the primary scientific authority.

Sources

Computer world

by Justin E. H. Smith · Hinternet · Read full article

Listen to our conversation on the Lapham’s Quarterly podcast, alongside D. Graham Burnett and Zena Hitz, on the familiar topic: “Whither the Humanities?”

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It was always bold, impudent even, to insist that material substrates or elementary particles could have what it takes to anchor reality as such. Perhaps the greatest propaganda coup of scientific modernity has been to convince a good number of us that such a claim is nothing more than right common sense, while any hesitation to affirm it could only be a symptom of soft-headed superstition or unhinged irrationality. To this extent I have long been perplexed by those philosophers who defend or at least toy with simulationism, and who seem to relish the small frisson of transgression it so reliably delivers to them. The suggestion that reality is more “bit”-like than “it”-like, seems to be experienced by its defenders as a relatively safe venture into philosophical edgelordism, making the majority normie philosophers cling to their “its” that much more desperately. The problem is not only that “its” were never at all well-suited to the heavy role of anchoring reality —what exactly, tell us, shouts “Being!” about an atom or mote or corpuscle?—, but also that historically their tenure in that role was relatively brief… no, it might better be said, they were still pre-tenure, and therefore still easy to get rid of.

It may be not, as simulationists have supposed, that we are discovering the true nature of external reality about which we had been uniformly wrong throughout all previous history, but rather that simulationist theories themselves are the predictable downstream narrative echo of a much more important historical process, namely: that we are transitioning out of the 400-year-long reign of physics as Prima Scientia. And the throne, some reliable indices suggest, is being usurped by what is for now still a multidisciplinary field of inquiry perhaps best identified as “information science”. One significant sign of the shift, as I and others have noted, came in 2024 when the computer scientists Geoffrey Hinton and John Hopfield won the Nobel Prize in physics “for foundational discoveries and inventions that enable machine learning with artificial neural networks.” I am myself no specialist, but as far as I can tell this is a research program more concerned with bits ...