The Alchemist, Philip Galle (after Pieter Bruegel the Elder) c. 1558 (source)
In 1965, Hubert Dreyfus wrote the first widely-considered critique of artificial intelligence, Alchemy and Artificial Intelligence, a report for RAND. He updated and expanded the work for broad publication in 1972 as What Computers Can’t Do (which was further updated and revised for two subsequent reissues) and a “sequel,” Mind Over Machine (in 1986). For a precis of Dreyfus’ views on AI, see here.
Adam Becker’s “More Everything Forever” begins by describing the ideas of Eliezer Yudkowsky, an AI guru who Sam Altman thinks deserves a Nobel Prize. Yudkowsky’s ambitions for humanity include “[p]erfect health, immortality,” and a future in which “[i]f you imagine something that’s worse than mansions with robotic servants for everyone, you are not being ambitious enough.” According to Yudkowsky and his peers, a “glorious transhumanist future” awaits us if we get AI right, although we face extinction if we get it wrong.
“AI” and “transhumanist” are new terms for rather older ambitions. As the seedy occultist Dr. Trelawney remarks in Anthony Powell’s 1962 novel, “The Kindly Ones,” “[t]o be forever rich, forever young, never to die … Such was in every age the dream of the alchemist.” Renaissance alchemists won the support of monarchs like Rudolf II, the Holy Roman Emperor who squandered his realm’s money on a futile quest to discover the Philosopher’s Stone. Now, as Becker explains, AGI, or artificial general intelligence, has become the means through which philosophers might transubstantiate our mundane reality into a realm in which the apparently impossible becomes possible: living forever, raising the dead, and remaking the universe in the shape of humanity.
These ideas would be a curiosity, if they weren’t reshaping the world, and policymakers’ understanding of national security…
[Farrell explains, elaborating on the beliefs in play and explaining how they played in the Biden Administration (which, he argues, largely internalized them) and now in Trump’s…]
… The Biden administration’s policies rested on risky bets. AI may not be the universal solvent for vexing and complex technological problems promised by Altman, Amodei, and their peers. Some (including most members of the Association for the Advancement of Artificial Intelligence, as well as myself and colleagues) believe that current approaches will not lead to anything like self-improving AGI anytime soon. As DeepSeek’s success in building AI models suggests, semiconductors may not provide the chokehold on AI that American policymakers believed.
In any event, the Trump administration has seemingly opted for a different approach, replacing a grand plan for a global AI order with a loose approach based on the ever-shifting convergence between notions of American greatness and the particular interests of well-connected companies. This currently involves leveraging control of technology to maintain American domination, cutting deals with Gulf states, while trying to cut China out. When Trump toured the Gulf states with an entourage of tech CEOs, he offered access to top-end semiconductors in exchange for promises of massive investment, graciously accepting a jet plane, and a large-scale money transfer routed, with fees, through his family stablecoin.
This emerging blend of imperium, magical technology, and self-dealing too is reminiscent of the Renaissance. The English wizard John Dee, who claimed to have turned mercury into gold in the presence of Rudolf II, is also credited with coining the term “British Empire.” As a member of the court of Queen Elizabeth I, he combined alchemical experiment and indirect conversation with angels with more mundane plans to extend British power across the Atlantic and enrich himself.
The alchemists’ quest for immortality and universal transformation is again entangled with the struggle among empires. The dreams of perfect health, the conquest of death, and mansions with robot servants that Becker describes inspire visions of a radically transformed far future and a near present in which America can use advanced technologies to bolster its power. Such visions stem from an ideology of salvation that has indeed fueled important technological advances but may be quite wrong about where those advances will bring us.
We are being ushered into a world where AI models offer new and useful means to summarize the information of the world and draw nonobvious connections across it, but can also weave new syncretic religious beliefs together from the myriad human sources that they summarize. In the early 20th century, Weber argued that rationalized Calvinism had led to the defeat of the old gods and the inexorable disenchantment of a world dominated by bureaucracy and organized capitalism. In the early 21st, just the opposite is happening as AI draws open the gate for the return of the fantastical. Yudkowsky’s eschatology is just one of the prophetic visions attendant on AI. The practical changes that AI will bring to bureaucracy and markets will go hand in hand with religious ecstasy and fervor, as some people come to believe that they can speak to God through the machine, while others use it to elaborate their own extended fantasies about politics. As Becker’s book shows, technology is not just an abstract force changing the world, but a mirror in which human beings see their dreams and ambitions made manifest. We’re starting to discover what that looks like at scale.
Then consider this, from Nicklas Lundblad, a senior exec at Deep Mind, Google, Stripe, and elsewhere, recently turned public policy Fellow. In a piece adapted from a lecture in a series of talks on the philosophy of artificial intelligence that he gave at Mid-Sweden University), he puts Dreyfus’s thought into context, tracing the history of arguments with/against it over the years, as both technology and thinking about technology advanced. He concludes…
… So, we may say, what is Dreyfus answer?… That he is obsessed with showing that machines are incapable of being human?
In fact, his conclusion, already in 1965 – and then repeated in the 1972 book – is much more interesting. Here is how Dreyfus concludes his critique:
If the alchemist had stopped poring over his retorts and pentagrams and had spent his time looking for the deeper structure of the problem, as primitive man took his eyes of the moon, came out of the trees, and discovered fire and the wheel, things would have been set moving in a more promising direction. After all, three hundred years after the alchemists we did get gold from lead (and we have landed on the moon), but only after we abandoned work on the alchemic level, and worked to understand the chemical level and the even deeper nuclear level instead.
Dreyfus’ answer is not to get stuck in the question of what computers can’t do – but to reject even that last piece of thick ontology and ask if we are making a fundamental conceptual mistake. He suggests that we find what is to intelligence as chemistry is to alchemy and look for another set of concepts, another language, to describe what we are doing.
We would, in Dreyfus view, be much better of trying to build alien intelligence or replicate animal intelligence or even jettisoning the idea of intelligence entirely in favour of a new concept – perhaps something like cognicity – that removes the Difference from the research program.
Dreyfus recommendations would imply that we should drop the benchmarks that distract us and instead focus on simpler, thinner ontologies around tasks and interactions. What we need, he would suggest, is a conceptual shift into that simpler ontology – at least if we want to make real progress.
The shift into modern machine learning seems to prove that when the thicker ontology was abandoned we did discovered things obscured by the idea of man as a symbolic animal.
What if we abandon both the idea of man and machine?…
As we think about transmutation, we might recall that it was on this date in 1954 (only 11 years before Dreyfus wrote Alchemy and Artificial Intelligence) that IBM introduced the “IBM 608,” the first calculating machine to use only solid-state transistors instead of vacuum tubes (thus needing only about 5% of the power to perform the same operations). The machine was housed in several large cabinets and could be purchased for $83,210 (or rented for $1,760 per month)… that’s just over $1,000,000 on an inflation-adjusted basis (or about $22,000 per month). It used more than 3,000 germanium transistors and could store 40 nine-digit numbers and perform 4,500 additions per second, among other operations.
Don Moynihan argues that here has been a shift in the character– the instincts, the motivations, and thus the patterns of decision and action– of our government…
One of the strangest moments to emerge from the U.S. kidnapping of Nicolás Maduro was the flurry of images posted by President Trump on Truth Social. It felt a bit like a student who can’t decide which spring break photos look cutest, so they just upload them all.
The intent seemed to be to create an iconic image reminiscent of the White House Situation Room during the raid that killed Osama bin Laden—a gathering of stoic men (no girls allowed!) staring grimly at some unseen screen. The message: “Look how serious and important our work is!” Yet, the staged nature of these photos undermines that effect, leaving the whole scene feeling less like history in the making and more like an amateur theater production of a Broadway classic.
In one image, the Director of the CIA, the Chair of the Joint Chiefs of Staff, and the Secretary of Defense are grouped around a laptop. Behind them, unmistakably, a screen displays a feed from X—complete with a prominent yellow emoji. In other pictures, “Venezuela” appears to be in the search box.
With the best intelligence systems in the world at their fingertips, they were checking X in the midst of the mission? Combined with the curtains separating some section of Mar‑A‑Lago from the rest of the President’s resort, the images create an almost surreal air. It felt as if a group of twelve-year-old boys in a basement had been handed control of the most lethal military in history—and were using it to boost their online brands.
Trump is undoubtedly the American president who has most effectively wielded social media: drawing attention, reshaping norms, and fueling conspiracy theories. The successful use of social media, for example, turned avowed MAGA isolationists into enthusiastic colonial imperialists overnight.
But I want to suggest that what we are witnessing from the Trump administration is not just skillful manipulation of social media—it’s something more profoundly worrying. Today, we live in a clicktatorship, ruled by a LOLviathan. Our algothracy is governed by poster brains.
It’s worth remembering that social media operates like a drug, feeding us dopamine and rewiring our brains’ reward pathways. The fundamentally unhealthy dynamics are worsened by the fact that standing out online often demands being awful—channeling negative emotions like anger and outrage, usually based on misinformation or conspiracy theories.
None of this is new. Indeed, there is a booming political science literature on the effects of social media on voter behavior. Chris Hayes and others have written persuasively about the how toxic attention farming is for us personally and for our democracy. But I want to make the case that we should also consider how social media it is affecting how policymakers use public power.
What I’m arguing is that the Trump administration isn’t just using social media to shape a narrative. Many of its members are deeply addicted to it. We would be concerned if a senior government official was an alcoholic or drug addict, knowing it could impair judgment and decisionmaking. But we should be equally concerned about Pete Hegseth and Elon Musk’s social media compulsions—just as much as their alcohol or ketamine use, respectively.
Overexposure to online engagement has cooked the brains of some of the most powerful people in the world. This is not exclusively an American phenomenon. President Yoon Suk Yeol seemed to have genuinely believed online conspiracy theories about election fraud, motivating his declaration of martial law and triggering a constitutional crisis, and his eventual arrest, in Korea.
But in the US government, poster brain feels endemic. The Trump administration is made up of a cabinet of posters. For many, that’s how they won Trump’s attention. The head of the FBI, for example, is a podcaster—that’s his main qualifier for the job.
They view the world through a social media lens in a way that is plausibly corrupting their judgment and undermining their performance. Lets think through how poster brain can affect how people in government operate…
[Moynihan explores, with illustrative examples, online bubbles, conflicts between professional and online indentities, the degradation of professional norms and work practices, and the altering of decision-making to be responsive to social media– to create content]
I’m just scratching the surface here. Pick any federal agency, and you can find examples of poster brains making important decisions. This trend is likely to only get worse as digital natives enter key government roles. And there are likely a host of other ways these patterns are undermining the professional behavior of people in government that I have not identified. In particular, the Trump administration represents the intersection of poster brain, personalism, and authoritarianism that seems especially toxic…
… The bottom line is that it we need to take more seriously how social media has rewired the brains—and behavior—of those running our country.
Your correspondent is headed onto the road again; so, with apologies, regular service will be suspended until on or about May 17…
… In the meantime, the remarkable Henry Farrell offers sage advice…
Last Thursday, Combinations (a publication of the RadicalxChange foundation), published a review essay that I wrote on Ezra Klein and Derek Thompson’s Abundance. I’m not going to repeat here what I say there; it’s available for free, so if you want to read it, just click on the link! [and one should read it]. Instead, I want to make the implicit argument explicit.
One of the big problems of American politics – and of politics in plenty of places elsewhere – is that we lack usable and attractive futures. The result is the current battle between the defenders of the present, and an incoherent counter-alliance that brings the cultists of an imaginary past and the evangelists of an impossible future into common cause.
Because I am weird, I think that the most immediately useful aspect of Klein and Thompson’s book is not its specific argument about how to get to the future. It is that the book has the promise to reorient the presentists around the prospect of an attractive future, and the different paths you might take to get there. On the one hand, as Dan Davies says (riffing on post-punk philosophizing), if you don’t have a dream then how’re ya gonna have a dream come true? On the other, no single dream is capable of foretelling the One True Path To Abundance (or, for that matter, any other desirable goal) so you want to have useful arguments between people with different dreams, and different plausible paths…
[Farrell discusses the book and its reception– the myriad reactions it has occasioned– puts the debate into an intellectualy historical context, then pivots to his advice…]
… One terrifying prospect for the U.S. is that the Trump faction wins again in 2028. Another is that the Democrats regain power – but that like Keir Starmer’s government, they trap themselves in a vicious cycle where universal expectations of less generate factionalism and political stasis, which further deepen those universal expectations.
That is why I think that abundance is important as a goal. We need to aim towards some version of abundance to escape the trap we’re in. That too, is why I think that disagreement about how to reach that goal over the next couple of years is valuable in two ways.
First, no faction on the left or right has any monopoly on the wisdom about how to get there. It is only through argument – and experimentation in those bits of the federal system and local politics where experimentation is possible – that we can figure out what to do when we can do it. Second, if we can get to a place where the major argument is about how to get towards abundance, not just between center left and centrists, but across the political spectrum, we – for a very broad value of we – will be halfway towards winning the fight we need to win. Far more is politically possible when we are disagreeing over how to get to an attractive future, than when we are struggling to ensure that we are as close to the top of the pile as possible in a horrible one.
We need usable futures that can orient current politics in fruitful ways. Abundance – in the broadest sense of that term – is the closest thing to a common denominator across such futures that I know of…
As we opt for optimism, we might send cautious birthday greetings to an example of what less-inclusive abundance can yield: John Warne “Bet-a-Million” Gates; he was born on this date in 1855. A Gilded Age industrialist and gambler, Gates was among the first salesmen of barbed wire. He parlayed his success into the manufacture of of the fencing; and success at that, into the manufacture fo steel. (He was instrumental in changing the steel industry’s production methods from the Bessemer process to the open hearth process.) He was the president of Republic Steel and later, of the Texas Company (an oil concern later known as Texaco) and of the Kansas City, Pittsburgh and Gulf Railroad.
Gates developed a taste– and a talent– for gambling at a young age. In his prime, he was known to host raucous, days-long poker games in his permanent suite at the Waldorf-Astoria. His nickname derived from a 1900 horserace in England on which he wagered $70,000 and was widely-reported to have won $1,000,000 (though it seems likely he won “only” $600,000).
… and how we do we create the conditions to encourage that learning? Industrial policy, one possible answer, is making a comeback. But as Henry Farrell explains, that raises another challenge…
… For decades, economists have argued that state policy makers lack the requisite knowledge to intervene appropriately in the economy. Accordingly, decisions over investments and innovation ought be taken by market actors. Now, the “market knows best” paradigm is in disrepair. It isn’t just that “hyperglobalization” has devoured its own preconditions, so that it is increasingly unsustainable. It is also that some goals of modern industrial policy are in principle impossible to solve through purely market mechanisms. To the extent, for example, that economics and national security have become interwoven, investment and innovation decisions involve tradeoffs that market actors are poorly equipped to resolve. There are good reasons why Adam Smith did not want to see defense policy handled through the market’s division of labor.
What we now face is a quite different kind of knowledge problem. We lack the kinds of expertise that we need to achieve key goals of industrial policy, or to evaluate the tradeoffs between them. This lack of knowledge is in large part a perverse by-product of the success of Chicago economists’ rhetoric. Decades of insistence that economic decisions be handed off from the state to markets has resulted in a remarkable lack of understanding among government policy makers about how markets, in fact, work. This has a variety of consequences. Policy mistakes are more likely. Market actors find it easier to manipulate the understanding of government policy makers, e.g. as to the extent and kind of subsidies required in particular sectors or for particular purposes.
One way to remedy this is to rethink the kinds of specialist education that public administrators receive, both to ensure that low and mid-level functionaries are better equipped to take the decisions they need to take, and to signal increased prestige for non-traditional forms of policy knowledge. As the sociological literature suggests, elite US policy schools such as the Harvard Kennedy School, Johns Hopkins School of Advanced International Studies and Georgetown University (to name three entirely random examples) play a key role not simply in directly imparting knowledge through education, but in disseminating norms about the kinds of knowledge that are considered to be appropriate for policy decisions. These schools have by and large converged on a framework derived from a watered down version of neoclassical [indeed. one might suggest, neoliberal] economics. I argue that new skills, including but not limited to network science, material science and engineering, and use of machine learning would be one useful contribution towards solving the new knowledge problem…
As we retool, we might send thoughtfully calculated birthday greetings to Paul Collier; he was born on this date in 1949. An economist who specializes in development, he is a professor at Oxford and director of the International Growth Centre.
Collier is a specialist in the political, economic and developmental predicaments of low-income countries, and is probably best known for his 2007 book, The Bottom Billion: Why the Poorest Countries are Failing and What Can Be Done About It. His philosophy, developed there and in his 2010 The Plundered Planet, is encapsulated in his formulas:
Regulation often addresses real public needs/concerns. But the costs of compliance often favor the largest players in a regulated market– which can lead to consolidation. From the Oxford Martin School, a current example…
Exploiting the timing and territorial scope of the European Union’s General Data Protection Regulation (GDPR), this paper examines how privacy regulation shaped firm performance in a large sample of companies across 61 countries and 34 industries. Controlling for firm and country-industry-year unobserved characteristics, we compare the outcomes of firms at different levels of exposure to EU markets, before and after the enforcement of the GDPR in 2018. We find that enhanced data protection had the unintended consequence of reducing the financial performance of companies targeting European consumers. Across our full sample, firms exposed to the regulation experienced a 8% decline in profits, and a 2% reduction in sales. An exception is large technology companies, which were relatively unaffected by the regulation on both performance measures. Meanwhile, we find the negative impact on profits among small technology companies to be almost double the average effect across our full sample. Following several robustness tests and placebo regressions, we conclude that the GDPR has had significant negative impacts on firm performance in general, and on small companies in particular…
As we seek balance, we might recall that it was on this date in 1969 that the U.S. officially withdrew $500, $1,000, $5,000, and $10,000 bills from circulation, pursuant to an executive order by President Richard Nixon. The larger bills had been used by banks and the government for large financial transactions, but had been rendered obsolete by the electronic money transfer system.
Those large-denomination bills were last printed on December 27, 1945 and are still considered legal tender. Indeed, (a version of) the $500 is still used in the game of Monopoly.
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