AI’s problems start at the top. Unlike the internet, which spawned a number of independent companies (including Google and Microsoft), AI seems to be controlled by existing tech giants, which are investing heavily in these new firms. ARM, for instance, the British-based chip designer whose IPO last week set Wall Street aflutter, is garnering huge investments from other Big Tech firms, including Nvidia, Intel, AMD and Apple. Elsewhere, Open AI’s largest investor is Microsoft, while DeepMind was acquired by Google in 2014.

This pattern of collaboration between giants and upstarts suggests that the next tech revolution seems poised to empower the existing hierarchy. It also threatens the prospects of the classes below. Big Tech and venture capital executives such as Reid Hoffman promise that AI will serve the cause of “elevating humanity”, despite potentially wiping out hundreds of millions of jobs worldwide. Indeed, according to McKinsey, at least 12 million Americans will be forced to find new work by 2030. In other words, AI looks destined to warp our class structure in a similar way to feudalism, turning what has been a collection of Roman citizens into serfs.

But is this the entire story? Historically, humans have performed analytical tasks manually. They may have created tools, such as spreadsheets and surveys, to help them. But the tasks of optimising businesses have largely lain in the hands of human analysts who spend their days collecting data on the performance of businesses and markets. In the last phase of technological development, jobs for these “symbolic analysts” exploded: in the US, the number of workers in occupations requiring average to above-average education, training and experience increased from 49 million in 1980 to 83 million in 2015. Yet these tasks are now running into a buzzsaw with AI, whose underlying premise is that machines can learn to detect patterns and changes better than human beings.

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The greatest generational conflict

By Joel Kotkin

In his bestselling book AI Superpowers, Kai Fu Lee, a former Google and Microsoft boss who now runs one of the world’s most prolific AI venture funds, proposed a two-dimensional view of the future of work. His key thesis: that the social nature of a job and the discretionary nature of a job will be the key factors underlying AI’s impact. If, for instance, a job is highly formulaic and has few discretionary decisions, and people perform their tasks with little social interaction, AI is likely to displace it. So, while the CEO of an insurance company might be safe from being displaced by AI, one of his analysts is not.

And this is where the nuance is often lost. According to the US Labor Department, AI and automation could impact as many as many as 90 million American workers, with warehouse workers among the most prominent losers. What will really alter class relations, however, is the impact on more professional jobs. They have been the ascendent class for the last two generations, growing at an average annual rate of 2.2% since 2001 — well above the 0.4% annual rise for total employment. But whereas the computer revolution was a boon to those working as programmers and market researchers, AI does the job for them, often with more speed and accuracy. As Rony Abovitz, one of the pioneers of virtual reality and AI, has observed: “It’s the end of the white-collar knowledge work.”

In such a world, it is not hard to envisage a new kind of class conflict that extends beyond the traditional Marxist conflict between low-wage workers and better-educated owners. More than 82% of millennials fear AI will reduce their pay, and they are right to be worried. “We may be at the peak of the need for knowledge workers,” Atif Rafiq, a former chief digital officer at McDonald’s and Volvo, recently warned. “We just need fewer people to do the same thing.” As if to illustrate his point, tech firms such as Meta and Lyft have already announced major cutbacks in their white-collar workforce, while IBM has paused hiring to assess how many mid-level jobs can be replaced by AI.

What this means more broadly isn’t tricky to discern: a once-rising class that often embraced the oligarchy’s ideas now faces the same kind of marginalisation experienced by less-educated workers for generations. And it is not unreasonable to conclude this could eventually divide the current political alliance between progressively minded professionals and the AI-enhanced elite. Perhaps the most visible example of this is the writers and actors strike — drawn from a class traditionally aligned with the oligarchs — currently underway in America, where AI threatens to make the manufacturing of entertainment largely redundant.

Indeed, tech executives are already planning for the emergence of a vast, unproductive class made largely redundant by AI and robotics. After interviewing 147 digital company founders, the technology journalist Gregory Ferenstein has concluded that an “increasingly greater share of economic wealth will be generated by a smaller slice of very talented or original people”, while everyone else comes to rely on gig work and government aid. This is reflected in support for universal basic income by a number of leading tech oligarchs — Mark Zuckerberg, Elon Musk, Travis Kalanick (former head of Uber), and AI guru Sam Altman (CEO of Open AI).

Of course, many might wonder what is wrong with this. Already, roughly half of all Americans support the idea of a guaranteed basic income of about $2,000 a month if robots put them out of work. UBI enjoys even stronger support in most European countries, particularly among younger people. Further east, the popular Japanese Marxist philosopher Kohei Sato sees re-distribution as a way to as achieve the green goals of “degrowth” and “net zero” without devastating the masses.

Yet if history is our guide, such intellectual circles are surely plagued by a certain naiveté. In every stage of capitalism, the ruling class has offered promises of welfare and support. And in every stage of capitalism, they have only done so with the intention of strengthening their own position.

What is different this time, though, is that there is one class of worker who remains capable of opposing this neo-feudal structure: those with hands-on yet skilled jobs, such as the engineers refusing to work at Intel’s new semiconductor facility in Ohio. After all, even the infrastructure for AI requires tactile skills, and, as a result, technically capable blue-collar workers still have leverage and can shut down the whole infrastructure. This same class of skilled artisans were at the vanguard of the rise of democratic capitalism. Two centuries later, they may be our best hope for resisting a very different revolution.

The messages had a brief heyday in 2016, making the rounds of New York City editors and literary agents, in advance of a public reading I gave in the East Village. In the cultural moment just before Donald Trump’s emergence, these half-baked far-Right musings were a novelty; alas, Trump’s presidential triumph scuppered plans to make an eBook out of them. But I still re-read them, when I want to remember the old man. (He had, of course, hoped that I would: “I send these because life and death is about MIND over MATTER…….&& I want to reMIND u that it don’t matter…..”) Perhaps it was loneliness that made me wonder if his voice could ever be resurrected.

In my day job, as a senior content manager for a research consultancy, I often use GPT-4. It is competent at various brute-force operations — turning lengthy transcripts into notes, proofreading content — even if the inputs require constant fine-tuning and the outputs require careful attention to ensure accuracy. But could it write content that would bring back the dead? Could GPT-4, if sufficiently trained, analyse my father’s emails — and perhaps even write new ones?

“Well well well, my BOY, let ol’ FOG lay down some KNOWLEDGE on the import-ants of self-defense!” So began one of the emails produced by GPT-4, after I fed my father’s archive into it. As an opening it feels slightly more stilted than the source material, and I can’t recall my father ever referring to me as a “BOY”, but he did call himself the “FOG” (short for “effing old guy”) and randomly capitalise entire words and hyphenate others (“import-ants”), though he would never have bothered with the apostrophe after “ol’” (he’d merely write “ol”).

I know my father’s voice when I see it — it is a script that runs in my own head, like a built-in AI. And as GPT-4 generated more missives, I was increasingly certain: it could not replicate my father’s erratic punctuation usage. The mere ellipse was never enough for him; he would sometimes type out a dozen full-stops or more. These time signatures often appeared in the long, quiet sections in the saddest emails he wrote: “Go out there and just outwit the bastards………Nothing else to Life…..every body loses but some people stay in the game for a long time and have a happy life and family….I never did…..oh well…I saw it and I read the writing on the wall……” It was these inconsistencies that enabled me to hear his voice, these peculiarities that made his work human.

I doubt that a machine will ever be able to mimic his syntax. But given the right prior inputs, GPT-4 could respond to questions or develop political platforms (or children’s stories) in a manner that eerily resembled my father’s thought process. Was this a true reanimation, or merely what University of Washington linguist Emily Bender, a critic of equating AI outputs with human reasoning, might describe as “stochastic parroting”? The AI certainly captured subtleties in my father’s work that I and others overlooked during that reading in the East Village. Listeners then likely saw him as some outsider-artist variant of Alex Jones, spewing rote conspiracy theory. But ChatGPT, when asked to summarise his politics, cut through the outlandish expression to a more comprehensible core: “Your father’s concern for the environment and the need for sustainable practices aligns with the environmentalist movement [while] his preference for local communities and self-sufficiency has some connections to localism.”

This was, of course, true, though I never thought about it in this way — nor did I consider that his “focus on gender equality and women’s empowerment aligns with progressive politics”. My father was the sort of man who moved to a “mountain house” in Montana to live out his final days; he was far closer to the libertarian Right of Karl Hess — who also retired to the wilderness — than the more culturally conservative, evangelical Right that dominated his era (or the MAGA movement that dominated mine). The AI analysed and reproduced a version of my father distinct from who I remembered. But perhaps there were things I had missed.

The progress AI has made in understanding and generating human-like text over the past six months is impressive — a great feat of engineering that will, in time, be remembered alongside the construction of the Pyramids or the Great Wall of China. However, AI models are still unable to mimic the voices of highly idiosyncratic, distinctive writers. The polymath University of Paris professor Justin E.H. Smith, for instance, has found AI largely incapable of simulating his unique voice. But in his case the content, rather than simply the form, of his communication is highly complex.

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AI is a false prophet

By Jacob Howland

The writing of Right-leaning political blogger Curtis Yarvin, on the other hand, appears stylish on the surface, but is often considered lacking in substance — a fellow editor noted that removing every other sentence from Yarvin’s excessively ornamental prose would not change its meaning in the slightest. Yarvin believes that GPT-4 cannot reason or think, merely discern and reproduce patterns. His writing, however, is undeniably replicable; a sentence such as “the only way to write about finance is to be either neither bull nor bear, or both” seems sophisticated at first glance, but it exemplifies what one of my old writing mentors might call “all sizzle and no steak”. In other words, Yarvin, like many commentators succeeding on the internet, can skilfully assemble sentences that can be skimmed for hours but forgotten in minutes — meaning that imitating his work is the ideal scenario for an LLM that ceaselessly creates a persuasive imitation of style, without any regard for substance.

The general public, most of whom skim content rather than paying attention to form, may struggle to differentiate between authentic and AI-generated content. More perceptive readers can sometimes detect minor discrepancies that reveal the artificial nature of the imitation — but even they aren’t perfect. In one study, researchers investigated if LLMs could be as good as humans at creating philosophical texts, by fine-tuning GPT-3 with philosopher Daniel C. Dennett’s works. While experts and philosophy blog readers performed above chance level in distinguishing Dennett’s answers from the model’s, they still fell short of the expected success rate.

The implications here are alarming. If most people are unable to distinguish between human-generated and AI-generated content, creativity and critical thinking will become rarer attributes. A new class divide could spring up, between the privileged few capable of discerning the nuances of AI-generated content, and a growing mass of individuals left to consume, without question, whatever is presented to them. The “priestly class” would consolidate power by reading between the hieratic lines of AI-generated content — just as the literate elites in ancient Egyptian and Sumerian civilisations did, by controlling access to sacred texts and legal knowledge. Their ability to recognise genuine information would give them a competitive edge in everything from financial markets to politics, further widening the gap between the informed and the uninformed. Meanwhile, the vast majority — an ever-expanding pool of digital-age helots left to hew wood and draw water — would become increasingly vulnerable to manipulation and misinformation. The forces that shape our lives would be less accountable, and it would be ever harder to address ethical concerns or make well-informed decisions.

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Why is my chatbot hitting on me?

By Kathleen Stock

Unfortunately, it is difficult to even imagine the mass education needed to achieve the necessary levels of discernment — much less its effectuation. Most people would rather be watching 15-second TikTok videos than close reading. And while a significant percentage of the world’s population will always, unfortunately, lack the cognitive skills or cultural capital to navigate our swiftly-changing content ecosystem, even the well-educated are in danger. We are witnessing a decline in the humanities, which traditionally turn future workers into critical thinkers, capable of discerning the idiosyncrasies in human expression.

As AI-generated content becomes increasingly sophisticated, we must prize those idiosyncrasies. They are, as I saw when I attempted to replicate my father’s emails, what make each writer’s voice distinct and authentic; they are the reason discerning readers might pay to read a mind-expanding Substack instead of boring, one-note op-eds or paint-by-numbers YA fiction. By embracing the unique aspects of the way they communicate, writers may create work that resonates on a deeper level, appealing to an audience that still wants to read the best work that humans can produce.

My father’s voice is one of a kind. But to find out if my conclusions are replicable by a machine, I decided to ask ChatGPT to provide its own opinion on the likelihood of it fully “replacing” a given writer. “It’s important to consider that my responses are based on patterns and structures found in the data I’ve been trained on, rather than personal experiences or emotions,” it replied. “As a result, even though I can generate text that appears to be in the style of a specific person, it is still an approximation and not a direct reflection of their thoughts or ideas.” Of course, when I am communicating with a machine that reproduces the thoughts of my dead father with a reasonably high degree of precision, it’s pretty to think it might be otherwise. But more alarming is the question I am left with: Could I have put it better myself?

I was born the year Margaret Thatcher came to power, 1979, and cast my first vote the year the man she called her “greatest success” scored his first landslide victory. Over my lifetime the contours of respectable politics have been defined by the joint trajectory they set. Now, 25 years after Blair’s landslide victory, it’s clear that his legacy is best understood in conjunction with hers.

Like Thatcher, Blair was animated by a powerful vision. His was also, like hers, a politics of the ideal: of elevating the abstract over the material world. And together, they’ve delivered a politics in which the ruling class has withdrawn en masse from engaging with the world as it is, preferring the world as they think it should be. Today, we live with the monstrous offspring of their combined economic and cultural politics of abstraction. Blending Thatcherite callousness for the politically weak with the providential self-righteousness of Blairism, their legacy has fused in a politico-commercial basilisk that proposes to rule us all: woke capital.

Many of those who, unlike me, remember the Seventies will tell you Britain’s economy wasn’t in a happy place back then. Britain was “the sick man of Europe”, all crumbling public services, sclerotic nationalised industries and rolling strikes. Thatcher’s leadership transformed this Britain, forcing the economy kicking and screaming away from earning a living by making stuff toward earning a living by manipulating ideas.

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New Labour was beyond parody

By Ian Martin

Deindustrialisation was brutally swift: between the second quarter in 1979 and the second quarter in 1981, manufacturing employment fell by 17% and manufacturing output fell by 20%. During her tenure, financial services rose from 15% to 24% of the economy, while manufacturing slumped from 21% to 17%. The impact was, as is now well-documented, not evenly felt. Knowledge-industry hubs such as London, Cambridge and Milton Keynes boomed, while those dependent on manufacturing languished. My childhood in the Home Counties was comfortable; my Liverpool-born husband remembers a graffiti slogan in the Merseyside of “managed decline” that read: “WILL THE LAST PERSON TO LEAVE PLEASE TURN OUT THE LIGHTS”.

The Old Left served as the political voice of workers in the real economy. But with the unions broken and industries privatised, that Labour Party was permanently crippled as a cultural force. Blair, though, carved out a new role for the Labour Party by transposing the politics of de-materialisation from the economic to the social domain.

Out went unequal power relations grounded in the material dynamics of labour and capital; in came unequal power relations based on abstract identity groups. But Blair’s politics of abstraction went well beyond the newfound emphasis on identities, to suffuse much less obviously political facets of the Nineties and Noughties zeitgeist. Notably, he radically accelerated the transformation Thatcher inaugurated of that quintessential material marker of place and belonging — a home — into an asset class.

When he came to power, the cost of a home was around four times the average salary, where — with a few blips — it had been for the best part of a century. Since then, with only a brief post-crash hiatus, that multiple has rocketed to eight times the average salary and continues to climb. London’s housing stock is now, notoriously, a store of value for the international overclass of oligarchs created by financialisation post-Thatcher, and subsequently courted by Blair.

In this era came, too, a joyful rush to “modernise” all the comforts of home. The ebullient aesthetic of “Cool Britannia” sought to drag everything from food to furniture, interior design and tableware, from the stodgy domains of function and tradition and subject it to the “creative industries”: a sector enthusiastically championed as a core powerhouse for the new, dematerialised, ideas-only Britain.

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The abject failure of Cool Britannia

By Mary Harrington

From the late Nineties through the mid Noughties, an aesthetic tidal wave swept over Britain, replacing anything even faintly suburban or Tory-coded (carpets in pubs, cream leather sofas, anything beige or burgundy for example) with “modern” lines and bright colours. Old things were all very well, but only once they’d been self-consciously “upcycled”: claw-foot bathtubs painted in “quirky” colours, or fish and chips given a Jamie Oliver makeover.

Meanwhile, Old Left rallying terms such as “community” and “solidarity” lost their grounding in physical work or geographies, and became abstractions accessible to all.

Nationhood was yanked free of anything organic, chthonic or — heaven forbid — ethnic, and given a “quirky” makeover so it, too, could serve as an access-all-areas abstraction.

There were Union Jack flags on everything, from cushions to Mini Coopers and Geri Halliwell, while “Britishness” was retooled so its previous connotations were recast as repellently “nativist” and low-status. A new vision of “Britishness” was promulgated in its place: more like a gym membership (or indeed a de-materialised asset class), compatible with free movement in the expanded European Union, and acquired simply by moving to Britain and paying your taxes.

Blair even incubated today’s ideas-only art world. Number 10 saw visits from the Young British Artists, whose controversy-courting works comprised nothing figurative or traditional, but artfully-titled pickled sharks and unmade beds: works of pure idea.

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Britain needed the Falklands War

By Dominic Sandbrook

Thatcher shifted us irrevocably toward rule by abstraction when she broke the unions and permanently disabled the Old Left’s industrial-worker power-base. And Blair, too, made his contributions to the politics of abstraction permanent — by restructuring Britain’s economy again, toward the over-production of knowledge workers.

He did this first by shifting university funding onto a loan model, then replacing the cap on student numbers with a target of 50% of young people attaining a degree. The entirely foreseeable effects of this policy have been much discussed since, and include grade inflation, credentialism, regional “brain drain”, and a proliferation of resentful, underpaid and increasingly radical young progressives, among many others.

On occasion, Tories in the current administration will gesture at fixing one of these problems. But just as Blair had no option but a leftism of abstractions, so the Tory administration that succeeded him is stuck with the machine that overproduces the unreality class. For the student loan machine serves a secondary function, as an off-the-books subsidy to areas devastated by Thatcher’s economic de-materialisation. And this is of such structural importance to the British economy that neither party can afford to turn off the spigot.

A second-order effect of this quandary is to entrench the mass immigration that accompanied Blair’s “gym membership” version of national identity. This policy is so unpopular among Britain’s rump of real-economy workers that it made a significant contribution to perhaps the strongest protest we’ve seen against the politics of abstraction to date: Brexit. But when status, funding, voice and other perks overwhelmingly accrue to the unreality class, who can blame young people from seeking the credentials to join it? And this in turn leaves a slew of vacancies in real-economy work, such as care and agriculture, that must be filled from somewhere.

Meanwhile, few among the elite retain enough of a foothold in the real economy to resist the now well-embedded cross-party domination by denizens of this world of pure idea. So, unsurprisingly, we find all manner of issues now split along the reality/unreality axis.

Lockdowns, for example, were experienced quite differently by those with knowledge-based jobs and those whose daily activities take place in the material world. Elsewhere, it’s hard to reconcile views on transgender rights between those who experience sex dimorphism as materially significant, and those who see it as a set of abstract social constructions.

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Cherie Blair's class war

By Joan Smith

Was Blair the architect of the burgeoning 21st-century elite war on reality, though, or just the avatar for a larger trend? Similar patterns can be seen across many developed economies: across the pond, for example, America had Reaganism and Clintonism. And recent debates in countries such as France and America suggest a similar divergence between a tone-deaf elite bedazzled by abstractions, and a resentfully subaltern class that still inhabits the much-deprecated real economy.

But even if Blair didn’t force this on Britain out of nowhere, so much as steer the country according to prevailing winds, he still made a unique contribution: a distinctively Blairish sense of providential moral certainty that now overlays growing swathes of the economic individualism Thatcher inaugurated.

For if Thatcher believed markets and privatisation would deliver improved services for the British public across the board, it was under Blair that the corporate world embraced the idea that commercial and moral incentives could be aligned, for the benefit of all. The “Third Way” didn’t just involve sweet-talking oligarchs for a bit more tax take, or a slew of costly and ineffective “market” mechanisms in the NHS, but also a full-bore drive to fuse morality and profit via “social enterprise” policy, a move that tilled crucial soil for what we now know as “woke capital”.

And of course what this means in practice is less businesses doing good, than vast corporations hectoring us about abstract things that don’t impact their profits (such as pronouns) while remaining as avaricious as ever about material things that do (such as the housing crisis).

So it was Maggie and Tony together who created the conditions for the 21st-century war on reality we’re all now enjoying — a war now exacerbated by the onrushing digitisation of everything. We can thank him, too, for a set of perverse political incentives that condemn half of Britain’s youth (more, if policymakers are daft enough to listen to him today) to perpetual indebtedness and a credentialist Ponzi scheme, while stranding the other half in a grim and prospectless gig economy.

But if there’s one achievement for which his name must be cursed down the ages, it’s for that air of ineffable smugness that drifts from those getting filthy stinking rich while claiming to make the world a better place. We can thank Tony, above all, for the fusion of self-dealing and self-righteousness that now hovers over the war on reality, and deafens the unreality class to the increasingly mutinous mutterings from below.

But is it?

Usain Bolt is certainly the fastest over 100 or 200 metres, but if he and his fellow sprinters were to compete in a major marathon, they wouldn’t stand a chance of winning. In 2016, it was reported that Bolt had never run a mile (in one go) – let alone 26 of them (plus 385 yards). At the middle and long distances, the top names change, and also the body types. Distance runners have long, lean muscles rather than thick ones, their wiry frames built more for stamina than explosive speed.

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How cricket ran out of time

By Jon Hotten

The most dramatic shift in competitiveness comes in the ultra running events – i.e. any race longer than a marathon. These include ‘conventional ultramarathons’ such as the IAAF-recognised 100km race, but also jaw-droppingly extreme events like the Montane Spine Race, which stretches 268 miles along the Pennines from Edale in Derbyshire to Kirk Yetholm in the Scottish Borders.

In these supreme challenges of endurance, women are competitive against men. Earlier this year, the remarkable Jasmin Paris completed the course in 83 hours, 12 minutes and 23 seconds – smashing the previous record of just over 95 hours.

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Who’s best at what is often a matter of time. From the less than 10 seconds of the 100 metres to the gruelling day-upon-day of the Spine Race, different people excel at different timescales. And not just in running.

It’s a subject that Malcolm Gladwell explores in two brilliant episodes (here and here) of his Revisionist History podcast. His particular focus is on America’s Law School Admission Test. The LSAT is a standardised exam that determines whether you get into law school – and also which law school. Needless to say, the most prestigious institutions take their pick from the highest-scoring candidates. And, of course, it’s the cream of the crop that get the plum jobs after graduating.

The podcast features a speech by the late Supreme Court Justice Antonin Scalia, in which he said that he only chose clerks from the top law schools because it was the surest way of not making a hiring mistake. The kicker was that his remarks were made at a law school that did not fall within this highest echelon; yet far from reacting with hostility, his audience laughed along merrily.

So an awful lot rides on one’s LSAT score. But what exactly does it measure? Well, you can see for yourself in the current sample paper. It doesn’t test legal knowledge, but rather reading comprehension and logical reasoning. There are five sections – including three sets of multiple choice questions used to calculate each candidate’s overall score. There’s also an unscored ‘writing sample’ (essay) section, which can be used by two schools as a supplementary means of assessment.

The fifth section is also multiple choice – but instead of being used to assess the candidate in any way, the results are used to assess experimental questions for use in future exams. The examiners use the results to ensure that the LSAT is an effective measure of aptitude for law school students. Eliminating bias is a further objective. For instance, a question on which there was a significant gap in performance between male and female candidates would be rejected for future use.

And yet, Gladwell argues, the LSAT is biased – towards those who can blast through the questions at speed. Each section has to be completed in a strict 35 minute time slot. Therefore it doesn’t just measure comprehension and reasoning, but rapid comprehension and reasoning.

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Which experts should we trust?

By Peter Franklin

This wouldn’t matter if a test that gave people more time to think produced much the same ranking of candidates. But what if time made all the difference?

It certainly does when it comes to physical challenges like running, and we can see a similar pattern in purely intellectual activities.

Gladwell gives the example of chess, which at the top level has an international ranking system established through competition. In a standard chess game, players have 90 minutes in which to complete their first 40 moves and 30 minutes for the rest of the game. However, there are various gradations of fast chess, in which players have much less time to make their moves. This changes the rankings significantly. The best player in the world in standard chess is not the best player in ‘blitz chess’ or ‘bullet chess’.

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In his 2011 book Thinking Fast and Slow, Daniel Kahneman describes two modes of thought: “system 1”, which is instantaneous and instinctual and “system 2”, which is considered and calculating. One doesn’t have to limit oneself to that particular dichotomy to see that time gives us the space to deploy mental abilities that can’t be hurried. For instance, time to think gives the top chess players the ability to mentally picture the branching permutations of how a game might develop multiple moves ahead.

Of course, most things in life are not like chess. Being unconstrained by the rules and logic of a gamified environment, they’re immensely more complicated. But that makes time to think all the more important. Human beings are capable of all sorts of things beyond the split second and the unforgiving minute – like empathy, insight, creativity, inspiration. We’d all be lost without them, but especially those in positions of power and responsibility who have to deal with a bigger slice of life’s complexity than anyone else.

And yet the means by which we select our elites are biased towards quick thinkers not deep thinkers. The LSAT is hardly alone in perpetuating ‘fast privilege’. Similar against-the-clock methods can be found everywhere from IQ tests to civil service examinations.

And it’s not just pure aptitude testing either. In theory, our universities test students on their knowledge of whatever subject they’re studying. But what manner of knowledge: profound or superficial?

Oxford University’s Philosophy, Politics and Economics (PPE) degree has been described by Andy Beckett in The Guardian as the “degree that runs Britain” – because so many members of the political and media elites are PPE graduates. There’s a very long list of them here, which includes David Cameron, Jeremy Hunt, Bill Clinton, Rupert Murdoch and Ann Widdecombe.

PPE students are required to ingest knowledge across a broad front and regurgitate it in the form of frequent essays, tutorial performances and exams. But though no soft option, it is a degree for generalists not specialists – and thus an all-too-fitting preparation for UK politics. David Willetts, another PPE graduate, describes British political life as “an endless recreation of the PPE essay crisis.”

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The problem with political journalism

By Peter Franklin

Writing about his book Bluffocracy (co-authored with Andrew Greenway), James Ball argues that Britain has “become a nation run by people whose knowledge extends a mile wide but an inch deep.” A reshuffle is always a good time to see their bluffing skills in action. Politicians walk into new jobs, pick up an unfamiliar ministerial brief and proceed to talk about it in parliamentary debates and media interviews as if they were life-long authorities on the subject.

Journalistic attempts to expose their lack of knowledge are usually thwarted because the interviewers are bluffing too – resorting to easily deflected gotcha questions, instead of deeper conversations that might reveal something important about what our politicians think (or don’t think).

Last week, Yascha Mounk floated the theory that the real problem with PPE and similar Oxbridge degrees is that they reward students for making deliberately counterintuitive arguments:

“…ambitious students at Oxbridge are taught to go for a First by doing something extraordinary. 

“And by far the easiest way of doing something ‘extraordinary’ is to make a spirited case for a counterintuitive (and probably wrong) conclusion.

“This pedagogical tradition is responsible for (or perhaps stems from) a lot of the best things about Britain… It’s why British commentators are rarely boring…”

However, he thinks it also encourages “influential people – including writers and politicians – and especially writers turned politicians” to make “fun cases for irresponsible positions”. Which, he suggests, is one reason why we’re facing the prospect of a no deal Brexit.

Mounk concedes his theory is “probably wrong” and, ironically, itself an example of making a clever argument for a wacky proposition. However, the serious point that can be made is that the quality most valued in our highflyers is the ability to assimilate as much information as possible in as little time as possible – and then reapply it with maximum speed and agility.

Whether it’s the debating society tricks pulled by our politicians, or the “delivery at pace” expected of our civil servants, or the ‘hot takes’ extracted from our journalists, or the frenetic workload of the corporate lawyer, what recruiters are looking for is processing capacity not understanding.

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In the wake of the global financial crisis, many books were written in an attempt to understand what went wrong. One of the best was A Call for Judgement by Amar Bhide. The argument is encapsulated in his Harvard Business Review essay, The Judgement Deficit – in which he says that while the decentralised, entreprising nature of capitalism saw off the centralising tendencies of state socialism, it then fell victim to a new kind of self-imposed centralisation:

“…one that is the work not of old-fashioned autocrats, committees, or rule books but of statistical models and algorithms. These mechanistic decision-making technologies have value under certain circumstances, but when misused or overused they can be every bit as dysfunctional as a Muscovite politburo. “

The most spectacular example is what happened to the financial sector:

“A host of lending officers used to make boots-on-the-ground, case-by-case examinations of borrowers’ creditworthiness. Unfortunately, those individuals were replaced by a small number of very similar statistical models created by financial wizards and disseminated by Wall Street firms, rating agencies, and government-sponsored mortgage lenders. This centralization and robotization of credit flourished as banks were freed from many regulatory limits on their activities and regulators embraced top-down, mechanistic capital requirements. The result was an epic financial crisis and the near-collapse of the global economy. “

It’s not that IT replaced all the people – humans are still an essential component of even the most advanced corporate systems. However, they have allowed a huge amount of previously human judgement to be automated and therefore centralised. A bigger proportion of the decisions that matter can be concentrated at the highest levels of management – allowing the financial rewards for such work to be concentrated there too.

A corporate operation that shifts the balance to IT-mediated systems as opposed to distributed decision-making by experienced human workers is also easier to scale-up. This allows markets to become increasingly concentrated in the hands of fewer, larger companies – meaning even more money for those at the top. It also means that corporate growth can be achieved by exploiting monopoly effects rather than investing in product improvement, which of course is bad for innovation.

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Innovators, though, are disruptive of centralised systems – which is another reason to select the knowledge class elite on their ability to think fast, not deep.

I realise I’m painting a picture of them as cogs in a machine, which isn’t entirely fair. These are highly able individuals and some of the most able – e.g. those recruited into top law firms, consultancies, financial institutions and tech companies – are very well rewarded. They’re also made to work punishing hours – a reflection of their scarcity value and the desire of a corporate system to get the most out of its most expensively purchased components.

What’s true of the business world has a parallel in politics – only in this context the centre hoards power for its own sake, not to maximise profit and executive pay. In theory, a government minister should be in a position to think deeply about the policies they’re responsible for, drawing upon the expertise of their civil servants and the experience of frontline workers. Armed with such knowledge they’d then be in a position to pursue meaningful reforms.

But anyone who’s seen government from the inside could tell you that’s not how it works at all. The purpose of most ministers is not to exercise judgement on any significant matter but to process and communicate decisions made in Downing Street and the Treasury – if only by rubber stamping the mechanistic actions of whatever slice of the civil service hierarchy he or she nominally oversees.

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Of course, no centralised system of control is ever so perfect as not to need running repairs and work arounds. There’s always a demand for those who can improvise solutions when things don’t run according to plan and where local circumstances present unanticipated challenges. Dealing with such situations requires both judgement and creativity – but only in service of the system. Those most capable of it rise through its ranks; until, that is, they mess up irredeemably – at which point they can provide one final service: as a scapegoat for the failings of the system itself.

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The crying shame of the way we select our elites is that our finest, most fertile, minds are being wasted. They’re either sidelined because they don’t excel at tests of quick thinking, or because they can think both fast and deep, but are kept too busy by the systems they serve to ever think the disruptive thoughts that they’re capable of.

Sometimes an independently-minded individual does break lose – defying the selectors to follow their own paths. The tech pioneers who dropped out of college to start-up disruptive enterprises are a classic example. The irony though, is that some of the companies they founded have become monsters – corporate behemoths exercising super-centralised control not only over their own business, but ours too.

Neoliberalism was meant to set the market free – and yet, despite the IT revolution, this is an era of stagnant wages, growth and productivity. In seeking an explanation, we should start at the gateways of the knowledge economy.