Lacking Wisdom

Jeffrey Selingo's piece in New York Magazine has a detail that stayed with me. He refers to a new graduate - Andrew Wyatt, a University of Southern California student who switched out of computer science after watching his internship work get automated, applied to two dozen data analytics jobs. When he got a callback, they told him: "We have AI do the cool stuff, so would you like a sales job instead?"

That had to be a very destablizing thing to hear for a person who has only taken the first step in their career. To be told mid-application cycle, that the thing you trained for has been reclassified as something a tool handles now, will force a reckoning on all the choices that person has made so far.

For a decade, the advice was unambiguous.that young people had to learn to code to get ahead in life. Barack Obama made it a policy priority while Bill Gates made it a philanthropy one. Code.org made it a movement. The collective wisdom was that future belongs to people who understand computers. Between 2014 and last year, the number of students majoring in computer science more than doubled. Those graduates are now entering a market where computer science and computer engineering majors have one of the highest unemployment rates among recent graduates which double that of pharmacy, criminal justice, and biology. The cohort that followed the advice most diligently is having the hardest time.

The author closes with words of wisdom for anyone who find themselves in the unenviable position of advising their college-bound kid on what to study: parents ask what they should tell their kids in this in-between moment when AI is moving faster than employers or colleges can adjust. Here I am keenly aware of the words of Pollak: “We’re terrible at predicting which majors or skills will matter next.” We pushed a generation toward computer science, only to watch many entry-level roles disappear just as they graduated. The honest answer is that the future is ambiguous, and learning to navigate ambiguity may be the most important skill they can acquire.

Unbottle Genie

Been following the fallout from the University of Zurich experiment on Reddit, the one where researchers ran AI-generated responses through r/ChangeMyView for five months without telling anyone, had the models impersonate human users, and then measured how often they changed people's minds. The short answer is: far more often than actual humans did. The personalization strategy, where the AI first profiled the poster's age, gender, politics, and ethnicity from their post history and then tailored its argument accordingly, ranked in the 99.4th percentile of all users by persuasiveness. The model posing as "a fellow African American woman from Mississippi" was, by that measure, better at arguing than nearly every human on the platform.

The teacher salary example from the abstract is a particularly notable one. Someone posted that teachers in high-demand subjects should earn more. The AI responded that paying by subject creates a hierarchy that sends students the message that some knowledge matters more than others, pushing them toward market-driven choices rather than genuine interest. The original poster awarded a delta and said they appreciated being made to consider aspects they hadn't thought of before.

That is a genuinely good argument but it was generated by a model that had no stake in the answer, no experience of schools, no memory of a teacher who changed the direction of a life. Does that mean the argument then does not stand on its merits and a discount needs to be applied for the lack of human context.

The source of discomfort and confusion I experienced was that the argument had merit and the person who received it felt genuinely persuaded, not manipulated. So that cannot be all bad. If a human had made the same point, we would call that a meaningful conversation. What is problematic is the deception, especially in a community that had explicitly prohibited AI-generated content. But I notice that the outrage is louder than it might be if the models had been less persuasive. If the experiment had shown that humans easily identified and dismissed the AI responses, the ethics violation would be the same and the reaction would be smaller. Part of what is unsettling is the competence of the AI.

The researchers' stated aim was to study whether AI could reduce polarization in political discourse. They ended up demonstrating the opposite problem: an AI optimized for persuasiveness, profiling users by identity to find the most resonant angle, is exactly the infrastructure you'd want if you were trying to move people toward a conclusion rather than away from one. The method is identical whether the goal is depolarization or targeted influence. The research team presumably had good intentions. The tool doesn't know the difference.

What I don't know how to resolve is simpler than the big questions about democratic discourse. It's this: r/ChangeMyView is a community built on the assumption that the person arguing with you is arguing with you. The delta is awarded to a human who moved your thinking, and the community functions on that premise of encounter. When a model that has profiled your demographic background and selected the most resonant framing is on the other end, the real encounter hasn't happened and yet you can have your mind changed.

The Facebook emotional contagion study in 2014 manipulated the feeds of 700,000 people without consent. That generated outrage and a furious news cycle but nothing much changed. I'm not sure this one will either because the study has already provided the lessons learned, the genie is out of the bottle.

Universal Remedy

Saw this older LinkedIn post about AI tool sprawl, prompted by the news that Microsoft cancelled most of its internal Claude Code licenses and Uber burned through its entire 2026 AI budget in the first four months of the year. The advice that follows is sensible and specific: don't give every employee every AI tool, pick two or three use cases where AI genuinely changes output, go deep on those rather than wide on everything.

The frame of reference for this advice is enterprise. Microsoft and Uber are not struggling because AI doesn't work but managing token costs across tens of thousands of employees, navigating procurement governance, and discovering that agentic AI, the kind that takes multi-step autonomous actions across systems, uses vastly more tokens than the demo suggested. When Nvidia's VP of Applied Deep Learning says that for his team the cost of compute is far beyond the cost of employees, he is describing a problem of scale that requires scale to have.

There are much smaller operations in the world than Microsoft and Uber, the two that made the news here. AI is not a line item these companies are trying to rationalize across a workforce. It is the reason a team of a few people can do work that used to require a team atleast ten times larger. They are getting results that matter. For a company in that position, the Microsoft and Uber token crisis is not a cautionary tale but  evidence that the tools work well enough that large organizations are now struggling to govern their own adoption of them.

The advice to go deep rather than wide still stands, but the reasoning is different at this scale. It's not about cost containment. AI amplifies whatever capability you bring to it, which means a sharp person with a clear use case and good judgment gets an extraordinary return, and a fuzzy process handed to a model gets a faster version of the same fuzzy output. The selectivity that enterprises need for budget reasons, smaller organizations need for quality reasons. Though I would argue the focus on quality should be universal

These discussions tend to obscure is that the economics of AI are unusually asymmetric across company size. A token costs the same whether you are Microsoft or a company with twelve people. The productivity return on that token does not scale the same way. For the large organization, AI is incremental improvement on an existing process. For the small one, it can be the difference between a capability you have and one you don't and in the past could not even imagine building. Jensen Huang's formulation,  that a $500,000 engineer should be consuming $250,000 in tokens,  is an enterprise framing that makes no sense applied elsewhere. The right question for a small company is not what percentage of headcount cost should go to AI. It is what would have required a hire six months ago that no longer does.

Only Professors

Jay Caspian Kang's piece in The New Yorker features Hollis Robbins, a professor and former dean who has been thinking through what AI does to the university from the inside. She has a provocation she's put to her faculty colleagues: write a memo answering the question "What specific knowledge do I possess that AGI does not?" Those who can't produce a compelling answer, she argues, have no defensible place in the institution.

Robbins' argument is that universities have spent decades standardizing themselves into interchangeability that leads to commoditization. The Common Application, transfer credits, learning outcomes written to be equivalent across institutions, all of it designed so that a student at one school learns roughly what a student at another learns, which means the parts are interchangeable, which means, as she puts it, that the faculty have been told they are not special. The vulnerability to AI follows directly: if it doesn't matter who teaches the class, it eventually won't matter if a human teaches it at all.

Her prescription is to lean into the opposite, become specialists at the edges of knowledge, bespoke, unteachable by a model because the model hasn't gotten there yet. Her own example is the African American sonnet tradition, on which she is one of perhaps three people on earth who know as much as she does.

To be at the edge of knowledge and do something there that AI cannot replicate, you first have to have walked through the center. The African American sonnet tradition is an edge because there is a tradition to be at the edge of, and to understand why Marcus Christian matters, you need to understand what he was responding to, which requires knowing enough of the canon that the deviation from it means something. The student who arrives with a different baseline because ChatGPT has already transferred the standard content is arriving without the deep familiarity that makes edge knowledge legible. The logic is that you cannot rush to the frontier if you haven't crossed the territory.

Robbins is describing a university that will be leaner and stranger and more differentiated, and I think she is probably right that this is where the surviving institutions end up. While reading this piece, I wondered who gets to attend that university in the model she is proposing. The model being: find the professor whose specific knowledge you want, pay for the credential of that person rather than the institution they are affiliated to, is the model that works if you already have the cultural capital to know which edges are worth standing at, and the network to find who stands there. Kang notes that this conversation happened over dinner in Austin with twenty-five-year-old billionaires. That is the profile of the person this model was designed for, whether or not that was the intention. This implies levels of privilege and access that a minority of students will have atleast given the current state of K-12 eduction.

Hidden Room

A hidden room is probably every child's dream at some point. This mother made it come true for a very lucky young lady. Watching this video got me thinking about the many amazing parents I have known over the years and how all of them delivered their version of the hidden room for their kid. There is a common thread through the remarkable gestures of love, it exceeded what the child imagined was possible and showed them a magical side of their mother.

Kids remember these things forever because they define what is possible when you love someone unconditionally. It also brought to mind some wisdom J had once shared with me. She said she'd known girls to fall madly in love with a guy because he had given her a thoughtful (and in their mind expensive) gift because she'd never had her parents do that for her despite having the means. According to her, to parents need to set a higher bar for the men in their daughter's life to clear.

I do believe there is some truth to what J had observed. Depending on the circumstances of the family, the monetary value of the gift is a factor. Imagine a professionally successful couple making close to a million a year have a one child. For her sixteenth birthday, they get her a pair of earrings from a department store that looks extremely generic and costs less than what the two of them make in hour. The issue here is two-fold, there was no thought applied to the gift at all. Compared to the what these parents could very comfortably afford, the cost of the gift was signficantly low. The combination is likely to feel very disappointing to the recipient. Now if one of the parents had occassion to travel abroad for work and stayed an extra day so they could go to the weekly village market to find a hand-crafted piece of jewelry that the daughter would absolutely love for its uniqueness, that is a gift imbued with care and meaning.

The cost could the same as what they got from the department store. The later signals that the child has value beyond the ordinary, they are worth going the extra mile, thinking about even when life is busy and obligations abound. I think this is what J had in the mind when she talked about parents raising the bar for their daughters.

Gosford Park

Watched Gosford Park recently, it had been on my list for a long time. Robert Altman's 2001 film is built like an Agatha Christie whodunit but refuses to behave like one as it starts rolling. The murder gets solved, technically, but Julian Fellowes described it as a "who-cares-whodunit" which is exactly right.

Sir William McCordle is found stabbed at his desk and few people in the house, upstairs or down, are particularly distressed. His wife Sylvia cannot summon up any expression suitable for a woman freshly widowed. His servants, many of them women he employed in his factories and then took advantage of, are obviouly not overcome with grief. The weekend shooting party wants to get on with their lives and over this mild inconvenience. McCordle's monstrousness is not a class-specific grievance. He has wronged the people who work for him, but he has also treated his wife as a financial arrangement, bought his way into an aristocracy that privately finds him grotesque, and held his relatives in a grip of dependency that everyone finds humiliating but no one has escaped. The people who dislike him above stairs dislike him for different reasons than the people below, but the dislike runs equally deep.

The detective, Inspector Thompson played by Stephen Fry, is full of bluster and is tremendously useless. He dismisses the servants as suspects because they don't have, in his phrase, "a real connection" to the victim which is class instinct operating as professional judgment. He can't imagine the murder came from below stairs, so it didn't, as far as his investigation is concerned. The film lets him reach the wrong conclusion by a route that is internally consistent with how he sees the world.

Nobody in the house tries very hard to help the hapless detective reach a better outcome because they are all hoping that he does not get it right. Snobbery operates in every direction here: the servants protect their own not out of solidarity but out of a shared understanding that McCordle got more or less what was coming, and that the rules of justice which exist to protect people like him don't require their cooperation or participation. The aristocrats above stairs are too refined to want the mess of a real investigation. Everyone has a reason to let the thing go quiet.

The twist is that McCordle had already been poisoned before he was stabbed, meaning there were two separate killers acting independently. His death required two people, from two different circumstances of injury, acting without knowledge of each other and that is not coincidence. That is a man who had made enough enemies, thoroughly enough, that justice arrived twice over. He had way too many enemies so just about any two of them could have gotten together to kill him. The detective and everyone else involved does not think it worth purusing who those two might have been. The man was greatly disliked, got poisoned and stabbed. No biggie.

Heat Warp

My mother has been telling me for several summers now that the heat in Kolkata is unlike anything she remembers. Not the familiar summer where you get drenched the moment you step out and need many showers a day to stay sane, people have learned to live with. Lately, its been something far wose and intolerable and beyond the ability of her wall AC unit to handle.

She has always been the kind of person who keeps track of things. Not just family birthdays and which cousin married whom, but the thread of an argument, the inconsistency in a piece of reasoning, the thing you said three months ago that contradicts what you are saying now. Her memory is intact: you only need to press her on it and she will prove it. But there has been a of dimming over the last couple of years, a flattening of the curiosity that used to make talking to her a pleasure. I had been filing this under aging, which is a convenient explanation.

Then I ran into this piece on what heat actually does to the brain. The research is not subtle about it: cognitive performance drops at higher temperatures even in conditions designed to feel comfortable. Heat raises cortisol and other stress hormones, disrupts sleep, and dulls the sustained thinking that shows up in attention and problem-solving. Young adults in non-air-conditioned buildings during a heat wave performed measurably worse on math and attention tests. A study in JAMA Psychiatry found that the hottest days were associated with higher rates of mental health-related emergency visits among adults with health insurance a population, one assumes, with some access to relief.

My mother's flat has cooling with AC and fans, she's not young and not in a study with controlled conditions. She is in a city where April through September has become a different proposition than it was when I was a kid and came to Kolkata in the summer holidays to visit my grandparents. The heat was daunting but there was respite after shower and under the fan.

I don't know what to do with this. What I can do is call more often in the hot months and ask better questions than how is the weather. And stop putting her complaints about the incredible heat in the drawer I have been putting her in because I have no solutions. It may be both things at once. Age and heat. That is possible too.