The classroom, not the script: on the most human skill in the age of AI
About: “The most human skill in the age of AI” — Maya Makarovsky, TEDxMIT. Watch on YouTube (15 min).
The argument
Maya Makarovsky opens by confessing her phone’s calculator history, and from there takes a short step to the question that carries the whole talk: if we already ask ChatGPT to draft a two-sentence thank-you note, what are we going to outsource next? The figure she picks to justify the urgency is a public-health one, not a nostalgic one: one in two adults experiences loneliness, with a 26% increase in the risk of premature death —the equivalent, she says, citing the WHO, of smoking fifteen cigarettes a day—. We have optimized how we communicate and not how we connect, and generative AI doesn’t invent that problem: it accelerates it, because it automates exactly the part of interaction we train the least.
Hence the inversion that gives the talk its title. The question isn’t how well we’re going to work with machines, but how well we’re going to work with people: if AI keeps absorbing technical work, what’s left scarce —and therefore valuable— is exactly what no engineering curriculum ever taught. Makarovsky builds a four-move playbook out of stories from her travels through MIT programs in nearly fifty countries: seek understanding before agreement (she goes as far as suggesting you ask a chatbot to explain the other person’s view before a hard conversation); expand the pie instead of fighting over its division (a bazaar negotiation that ends in a cross-sale for the vendor); diversify your circles (a mixed team of engineers and business people building a mill for a women’s collective in Ghana); and, the simplest to name and the first to be dropped under pressure, show that you care. Worth watching: fifteen well-argued minutes, with concrete examples and without the usual solemnity of the TED genre.
The format, not the script
There’s something the talk illustrates without saying, and it’s worth naming right now, when AI is making content cheap to produce and format expensive to sustain. None of Makarovsky’s four points reached her as loose information: it arrived embodied in a structure that someone designed, funded, and sustained over time. The negotiation course she mentions (11.011, a semester with a fixed instructor and classmates) carries far more weight than the four-line summary you can pull out of it. The program that sent her to Ghana (MISTI) meant months of living alongside the same team around the same problem, not a portable anecdote. What produces the disposition to negotiate well at MIT —not just the list of tactics— is that community sustained over time, and it’s exactly the first thing cut when an institution feels the pressure to “do more with AI,” because it doesn’t fit on a slide: the four-point script survives, compressed, quotable even by a chatbot; the semester with an instructor, the funded trip, the team assigned for months, does not.
To speak, to speak with each other
I agree with the central thesis, and I think it needs saying out loud: as everyday conversation starts being delegated to the model, learning to speak —to negotiate, to listen, to concede without losing— is a skill that has to be practiced on purpose or it atrophies. But the talk frames it as an individual advantage (“the real advantage in the age of AI,” she says, in the vocabulary of employability), and that’s where it’s worth pushing a step further. It isn’t enough for each of us to learn to speak better if we learn it to compete better in the very market AI is narrowing; we also need to learn to speak with each other: to sustain a collective conversation that doesn’t dissolve the moment the project that convened it ends, one that decides together what’s worth discussing rather than just how each person negotiates their own share better. That distinction, between conversational competence as personal capital and community as a structure that endures, is again what MIT’s own format demonstrates without saying: what made Makarovsky a better negotiator wasn’t a technique she applied alone, but having been, again and again, obliged to talk with others inside a structure she couldn’t walk away from halfway through.
What remains open
The talk’s two most vivid examples —the bazaar haggling, the mill in Ghana— are, besides being legitimate illustrations of “expanding the pie” and “diversifying your circles,” transactions that run in a single direction. An MIT team travels to the global South to build infrastructure for a women’s collective and comes home with the leadership story; whoever already has the plane ticket and the institutional program behind them (MISTI) is the one who practices, at no cost to themselves, the skill of “diversifying your circles,” and whoever keeps the mill doesn’t necessarily also keep the story. None of this makes the recommendation false —the mill works, and the bazaar negotiation was real and benefited both sides—, but it does leave open a question that fifteen minutes can’t get around to asking: whether the program Makarovsky proposes can be carried out without deepening exactly the distance between the global North and South that her own examples, without meaning to, illustrate.