Audited Hype

Read a Guardian piece by Samantha Oltman arguing that AI absolutism, the tendency to see the technology as either civilization-ending or civilization-saving, is itself a product being sold by the people who stand to profit from the panic. The argument is sensible as far as it goes. Dario Amodei predicting that AI is "a general labor substitute for humans" while also running the company that makes the labor substitute possible is a conflict of interest. Jensen Huang telling people they won't lose their jobs to AI but will lose them to someone who uses AI is the kind of formulation that sounds reassuring until you think a little deeper about that means for you or your children.

Oltman quotes Columbia economist Suresh Naidu and UC Berkeley's Martin Beraja to argue that the job displacement numbers are overblown, that tech layoffs had more to do with pandemic-era overhiring than with AI, that software is only 4 to 6% of GDP so Claude Code can't eat the whole economy. While all of this may be true, "the apocalyptic scenario hasn't happened yet" and "the apocalyptic scenario won't happen" are very different claims, but the piece treats them as interchangeable. Sam Altman walking back his predictions about entry-level job displacement is presented as evidence that the fears were wrong. It's equally evidence that the technology is slower than advertised, which is not the same thing knowing for a fact that it is harmless.

Gig workers being managed by algorithm, the gradual extension of that model to white-collar work, the use of AI to extract more productivity from people who are supposed to feel grateful for the extraction: are things that are already happening. Oltman mentions it and moves on to a hopeful paragraph about "a lot of different little AIs from little responsible players" and the possibility of a labor movement resurgence, neither of which she has any particular evidence for. The Industrial Revolution analogy at the end, that worker solidarity eventually won concessions even if it took time is an useful one.

I've worked in IT long enough to remember when "the internet changes everything" was also a claim being made by people who stood to profit from the panic and the enthusiasm in equal measure. Some of what was promised happened much of it didn't. What nobody could predict was which parts, or on what timeline, or who would be left holding the bag when the timeline slipped. The Guardian piece is right that AI absolutism is a marketing strategy. It's just not right that the corrective is a different set of confident predictions about where things are headed. Naidu is quoted saying there's no control group for what we're living through and that is a very honest assessment.

Running Stitch

My grandmother kept a trunk full of old sarees so worn they'd gone translucent at the folds. When she enough of them accumulated she'd them to a woman in the neighborhood who made kantha quilts, layering the cloth into something thick and warm with running stitches keeping all the layers in place. The finished thing would go to a grandchild, or to the bed of someone who'd just come home from the hospital, or simply back to her to sleep under.

I read about Project Repat recently, a company that turns old t-shirts into quilts, sewn at Opportunity Threads in Morganton, North Carolina, a worker-owned cut-and-sew cooperative. The origin story involves a Nairobi traffic jam, an overturned rickshaw, and a Kenyan man wearing a shirt that said "I Danced My Ass Off at Josh's Bar Mitzvah," which is honestly the most American object one can encounter anywhere in the world. The founders started by working with Kenyan artisans on upcycled products to sell in Boston, discovered that nobody actually wanted a repatriated t-shirt bag, and pivoted when customers kept asking instead for quilts made from their own shirts. So now that's what they make. The word "repat" they've folded into repatriation, bringing textile jobs back to the US, which adds a political valence to what is at heart a very old impulse.

The kantha tradition in Bengal isn't quite the same thing. Those saris my grandmother saved weren't random accumulations. They were hers, her mother's, her mother-in-law's and had stories about them. The women in the neighborhood who stitched them knew whose wedding sari was at the center, whose daily cotton was at the edge. They had known my grandmother since she arrived there as a new bride right before partition. These ladies were refugees like her but much more deeply impoverished. This was the way the community pulled together in hard times. Project Repat is working with the same grief about discarded cloth, the same refusal to let memory just go to landfill, but the shirts are collected individually and the customer sends in whatever pile has been sitting in a drawer since forever. The stitch is performed by strangers earning a fair wage in North Carolina, which is its own kind of good bit it creates a different relationship to the object.

The average American discards 65 pounds of clothing a year, and most of it goes nowhere meaningful. Kantha quilts survived in Bengal partly because cloth was expensive and partly because the women making them had time structured differently than ours, long afternoons and meandering conversations that could accommodate slow handwork and spending time together while earning a living. Project Repat has found the American version of that instinct, outsourced to skilled hands in a cooperative in the Blue Ridge foothills, shipped back in a flat box. My grandmother would probably find it a little impersonal and would also be very pleased that the shirts didn't end up in a landfill. Given her life circumstances she simply could not abide by waste. 

Rocks Removed

Read Allison Johnson's piece in The Verge about vibe-coding a backyard app, and felt it was really about what it means to understand a problem before you try to solve it. She spent an afternoon in Google AI Studio building an Android app to manage her unruly yard, got a working preview in minutes, and then spent the next several days discovering that the app couldn't edit chores once created, that date pickers didn't pick dates, that Gemini had chosen black text on dark purple because legibility is not a concern for the the computer.

She'd asked for weather integration and Gemini offered her preset "climate profiles" instead of a live API call. It knows weather as a concept but doesn't know that it's 94 degrees right now in your specific zip code and the soil is already dry. She had to insist, more than once, that the physical world was the point of her application but the AI kept offering her a reasonable-sounding approximation of the physical world, which is a different thing entirely and nearly useless when you're standing in your yard in full sun trying to save a your herb garden.

I spent a good part of my career in IT architecture, which meant a lot of time watching people build systems for problems they'd described which were always the symptoms of the root cause they did not know existed. Root cause will bring on edge cases and contradictions and a bush near the front door that's dying for reasons the landscaper didn't mention when he took the cash discount and covered everything in river rock. Allison got there eventually, spent a sweaty afternoon raking back the rock and cutting the landscape fabric, and reported seeing new leaves on the rhododendron a few days later. The AI was right about the diagnosis biut the fix was still her hands in the dirt.

She ends the piece wondering whether the whole thing could have just been a Gemini chat and a to-do list in Google Keep, and I think she already knows the answer. Going through the process, she also learned something about her yard that she wouldn't have learned otherwise, which is that the shrubs were being slowly cooked from above and suffocated from below, and that pulling a weed out roots and all is, apparently, addictive. I find that more interesting than the app.

Yogurt Rounds

Watched an Al Jazeera short this morning about kodokushi, the Japanese term for dying alone and undiscovered, sometimes for days. Last year nearly 77,000 people were found dead in their homes that way. The segment showed Toyama Heights, one of Tokyo's oldest public housing estates, where an 88-year-old named Setsuko Kurahashi has lived alone for fifteen years, her children grown and elsewhere. A yogurt delivery company has become part of the social infrastructure there, the brief doorstep exchange the only human contact some residents get before noon. The deliveryman said they report to the company immediately if someone seems unwell. A wellness check embedded in a dairy route.

I kept thinking about my favorite grand aunt in her last years, how she talked about being alone and the phone or doorbell never rang expect when the milk was delivered and the maid arrived in the afternoon to help her with chores. She was not isolated the way Setsuko-san is, she had neighbors and a building with life in it, but there was that unmistakable silence of an elderly person's apartment in the late afternoon that I still remember from visits. To an outsider like me stepping in for a few hours, it could register as peaceful but I doubt if that is how she'd describe it.

Japan has a Minister of Loneliness now, a position created in 2021, and a billion-dollar industry of conversation platforms where you book time with someone to talk to, not for therapy but just for company. The piece framed this as a response to crisis, which it is, but it's also an admission that something ordinary and once freely available has turned into a paid service. There are younger people using these platforms too, not just the elderly, people under work pressure with shrinking social circles who find it easier to schedule connection than to stumble into it. I don't know how to feel about human conversation as a service.

Kolkata was loud and intrusive in ways I spent years wanting relief from. Neighbors who arrived without calling, relatives who stayed too long, festivals that made sleep impossible for a week. I live in a quieter place now, which I chose, and I don't regret the choice. But watching Setsuko-san wait by her door for the yogurt man, I find myself wondering what the people who designed modern urban life thought would fill that space, and whether they thought about it at all; if there will come a time in my life when I will want that loud and instrusive world I left behind decades ago.

Liability Theater

In Wired article I read recently, a Munich court ruling that Google is liable for defamatory statements its AI Overviews generated about two publishers. The AI had invented unsavory connections between them that appeared in none of the sources the Overview cited. The court called these "the defendant's own statements." Google, naturally, is appealing.

A Frankfurt court had already established in September 2025 that a search engine provider could theoretically be held liable for false AI summaries, and Munich followed with the logic that if Google builds the AI and controls its algorithms, Google owns what it says which is sensible and obvious enough. All that said, the ruling doesn't contend with is what Google has always been, and what it has no interest in stopping being.

The "Don't Be Evil" motto was retired in 2018, though in practice it was gone well before that. Google has been through antitrust rulings, publisher revolts, privacy scandals that would have destroyed smaller companies. It has carried out a systematic demolition of the open web it once claimed to be indexing rather than replacing. The Independent Publishers Alliance filed an EU antitrust complaint against AI Overviews in 2025, accusing Google of using publisher content without consent or payment while reducing their readership. Chartbeat data tracking thousands of news sites showed Google search referrals fell by a third in 2025, and some publishers have reported click-through losses approaching 90 percent for certain queries. The EU finds these practices concerning, regulators write letters and courts issue injunctions. Google appeals everything and continues operating exactly as before, because it is large enough that even losing costs less than changing higly lucrative behavior.

Pew Research found that when users encounter an AI Overview, they click a traditional search result 8% of the time, compared with 15% when there's no AI summary. They click a link inside the AI summary itself in 1% of visits. Google's argument has been that users could simply check the sources themselves, verify the AI's claims, do the work that the AI was supposedly doing for them. The Munich court was unimpressed: the ability to disprove a statement through further research does not, as a rule, remove liability for making that statement in the first instance.

What the court treated as an aberration that is actually the product. The people using Google Search are not customers because are the inventory. The actual customers are the advertisers though Google has not been particularly munificent towards them either. The user behavior gets packaged and sold, and the AI Overview is not a service improvement but the mechanism for keeping people inside Google longer, reducing the number of clicks that leave Google's ecosystem, and extracting more advertising surface area from each query. The Munich publishers lost traffic because reducing outbound clicks is Google's stated design goal, and the AI Overview is its most efficient implementation yet.

Google has also been appealing a separate November 2025 German antitrust ruling ordering it to pay roughly €572 million in the price-comparison sector. The appeals process, for a company with Alphabet's balance sheet, is just a small line item. The EU has been treating these rulings as major inflection points, moments when Google is brought to account and made to answer for itself. I don't know how anyone still believes that change is immiment when the previous twenty years of rulings produced no durable results at all.

In the Munich court judges drew a parallel to press law, reasoning that a misleading teaser headline is actionable even if the reader never clicks through to the full article and that AI Overviews function similarly as self-contained statements with independent meaning. That parallel is useful because newspaper that libels someone cannot defend itself by printing the source documents on page 12.

Whether Google will be moved by this particular framing is whole another question. The preliminary injunction will be appealed, the appeal will take years, and in the meantime AI Overviews will continue answering queries for hundreds of millions of users who have no reason to believe the confident paragraph at the top of their search results is less reliable than the blue links below it. Google offered more source links inside AI Overviews recently as a gesture of goodwill, which is the kind of thing you do when you are trying to look like a company that takes the problem seriously without actually taking the problem seriously.

The EU wants to believe it has found the right legal theory, the one that will finally make the accountability stick. I'd find that more convincing if Google hadn't already spent two decades demonstrating that it can hold every legal theory at arm's length indefinitely while continuing to do what it was doing before. They wrote the book on this and big tech has learned to follow it well.

Great Books

Naomi Kanakia's What's So Great About the Great Books? has been sitting in my reading queue since I saw her mentioned in that New Yorker piece about Substack novelists. While I didn't get to it, I did get to Todd Shy's review of it in the American Scholar this morning and it got me thinking about my own reading life.

Shy's says the real battle isn't whether Milton or Morrison belongs on a syllabus but whether we can preserve the practice of patient reading at all. Professors, he notes, have started mourning their students' lost capacity for sustained attention. In high school, reading gets taught as a skill to master rather than a habit to keep. It's no surprise that the skills wears off soon and the habit does not get the time to form. J grew up watching me read all the time and I was always a chronic over-sharer about what I'd read and what it meant. She was curious and sometimes I wondered if I shared less, she'd want to dive into the book herself. Whether any of what I did modeled anything useful for her, I genuinely don't know. She reads but very differently from me. Her attention is naturally distributed across more surfaces than mine ever was.

What Kanakia is apparently arguing is that the Great Books earn their status through what she calls "unflinching honesty" and "a certain seriousness." This is the thing that's hard to explain to someone who didn't grow up around books as furniture, as atmosphere. The difficulty is the point of taking on a challenging book. For readers who enjoy that experience, it is not about the prestige or cultural capital. In my most intense years of reading, I found it awkward to share what I was reading and why it mattered to me. As a mother, it beame easier because I had a captive audience and my goal was to impart a lesson not seek social cohesion.

All my reading is on screen now and that includes Kindle but it is not without value. The lack od attention is just the surface symptom of the discomfort of being in a text that doesn't immediately reward you. We've got very little tolerance for that now, and not just among students. I notice it in myself. I'll put down something demanding for something that requires less, not because I'm incapable of the harder thing but because the easier thing is always right there, always available, always frictionless. I grew up in a time when that was not an option so I learned to hunker down and do the hard thing. That has not been the case for a long time now so readers have not built the muscle for difficult and those like us can sense the atrophy.

Shy ends his review with a paraphrase of Oliver Twist: More, please and that feels perfect in the context.

Silent Contraction

A copper container of water sits by the doorway of my mother's flat in Kolkata, a small ritual against the dust of the city. When we speak on the phone, she mentions how the quiet has settled into the neighborhood because there are very few children and too many homebound old people, a silence that mirrors the statistical shifts now tracking across the subcontinent. Twenty years ago, that copper pot and her tray of fresh floating in water, which also sits near the door would have been like magnets to little children running up and down the staris. Today there is no chance that anyone will touch them even if they are gone for days. She misses that energy in her surroundings. My parents chose to live in this community because people of all ages live here. 

The newest data reveals that India has crossed a threshold many thought impossible during the anxieties of the twentieth century, with its total fertility rate dropping to 1.9, well below the replacement level of 2.1. While the overall population of 1.45 billion will continue to rise temporarily as the current generation of youth reaches adulthood, a significant contraction is on the horizon, with urban centers like Delhi already seeing rates as low as 1.2.

This shift challenges decades of demographic assumptions that linked population decline exclusively to Western wealth or East Asian corporate cultures. In India, the contraction is occurring at a much lower per-capita income level, driven not by women delaying marriage for careers, but by a profound transformation in parental aspirations across all economic strata. The traditional expectation of large families has given way to what economists call the quantity-quality trade-off. Parents are choosing to have a single child to concentrate limited resources on private schooling and tutoring, a trend visible even in poorer northern states like Bihar and Uttar Pradesh. The rapid transition from multi-generational households to nuclear families has further increased the daily burden of childcare, while the spread of digital media and smartphones has quickly normalized the cultural ideal of the small, urban family.

The domestic consequences of this transition will reshape the social and political fabric of the country long before it achieves widespread prosperity. Southern states like Tamil Nadu and Kerala are aging rapidly, with shrinking school enrollments and an expanding elderly population that lacks a comprehensive state pension system or the traditional safety net of extended family care. This regional imbalance is accelerating internal migration, drawing young workers from the north and east to fill labor shortages in southern factories and care facilities, a movement that complicates regional politics and strains local identities. Politicians have begun offering financial incentives to encourage larger families, yet global precedents suggest these measures rarely reverse deep-seated cultural shifts. The country faces an altered future, leaving open the question of how a society built on the momentum of youth will manage the quiet approach of its own contraction.

Too Wonderful

No prescription access to GLP-1 drugs at low cost monthly subscription is a new workplace benefit I've started to hear about recently. Many folks I know are enthusisatic specially the ones who would not qualify for the prescription because they are not severely overweight. They can now get in on the wonder drug of our times or so they make it sound.

Mayim Bialik published an essay in The Free Press about what happened after she took a single injection of the lowest dose of a synthetic GLP-1. She has a PhD in neuroscience, had researched the drug before starting and knew the pharmacology. She took it not for weight loss but because multiple doctors suggested it might help with health conditions she has been managing for years, Graves' disease, a connective tissue disorder. One shot left her unable to keep down water for weeks. 

Explosive diarrhea, sulfur burps, full-body aching, snatiation (a sneezing reflex triggered by eating), which apparently is a known side effect, but her doctor did not mention. She eventually needed IV fluids. The way she describes her acquaintance loving the clearly horrible side-effects sounds familiar:

I know many women who would not be considered overweight by any reasonable measure but are on these drugs because in Los Angeles anything over a size 4 is considered hefty. One acquaintance was thrilled that her GLP-1 made her so nauseous that she was barely able to eat at all, because it meant the pounds fell away even faster, leaving her thinner and happier than she had ever been. Another friend described the quieting of what those of us with disordered eating call “food noise”—the relentless mental chatter that accompanies every meal.

I've had a couple of women in their 50s and 60s tell that the one of the benefits colonscopy is that helps them lose weight. The actual point of the procedure was glossed over. The situation with GLP-1 sounds a lot like that expect the weight loss benefits continue. These women were not obese either, just not whatever size they have in mind to look physically perfect.

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.