This newsletter is brought to you by Squarespace.

For the past few years my “personal website” has been a publicly accessible Google Doc--a strategy that has great benefits, like ease of updating and rough charm, but also drawbacks too obvious to even mention here.

So recently I set out to make a personal website with Squarespace. (You can see it here.) Not only does Squarespace give me built-in S.E.O. and analytics tools--two things that my, ah, previous website didn’t offer--it’s nearly as quick and easy to update as editing my Google Doc site. I can even use my site as a storefront whenever I start selling Read Max merch again. (Soon, I promise.)

Most importantly, though, I wanted to maintain the unrefined, early-web charm of my Google Doc. W hile it would have been very easy to create an elegant minimalist site that reflected well on me using Squarespace’s beautifully designed templates, the tools Squarespace offers are powerful and customizable enough to let me build a site that looks as weird and cool as I had been hoping, including using a bunch of pictures my kid made on KidPix. So don’t let the tasteful professionalism of your friends’ sites fool you--you can get as weird as you want on Squarespace.

If you need a website, portfolio page, storefront, or nearly anything else, Squarespace is perfect. The only thing it can’t provide is KidPix images my son made.

Click here to try it out, and when you’re ready, use READMAX to save 10% off your first purchase of a website or domain.

Greetings from Read Max! This week’s newsletter is about guaranteed income, and how it fits in to the A.I. future.

A reminder: The above advertisement notwithstanding, the vast majority of my income comes from paying subscribers. If you enjoy Read Max and find it “valuable” to yourself, why not actualize that value in the form of money, specifically, $5 a month or $50 a year, which go directly to me and allow me to buy groceries, pay for housing, rent bad movies on streaming, etc. The income provided by paying subscribers allows me to actually focus on the newsletter, ensuring a smooth delivery of roughly 5,000 mostly coherent words every week. If you want Read Max to keep going, please consider subscribing!

I recently joined the Economic Futures Cohort at the Economic Security Project, a think tank dedicated to advancing “ideas that build economic power for all Americans.” In exchange for a stipend, I’ve attended three E.S.P. briefings and written about what I’ve learned and how I’m thinking about it. (E.S.P. has no editorial oversight; I have complete control over what’s published in this newsletter.) The most recent briefing was about guaranteed income.

This week in New York magazine, James Walsh has a feature about the bleak, disintegrating world of work now faced by a new generation of entry-level workers. He speaks with a 26-year-old who spent four years building worker-replacement automation software for PricewaterhouseCoopers, only to be laid off himself. (The kid is now “a kind of layoff influencer,” natch.) He talks to a 24-year-old who is made to use A.I. for her job, despite the shoddy output. (Her boss tells her “You should be talking loudly in the office about using AI.”) All in all, Walsh does not paint an optimistic picture for Generation Z. But the Zoomers’ bosses seem positively gleeful:

The extent to which recent layoffs are the result of automation is contested, but plenty of executives have nakedly blamed AI. Klarna CEO Sebastian Siemiatkowski says AI helped him shrink his workforce by 40 percent. Marc Benioff suggested AI agents were responsible for 4,000 job cuts at Salesforce, and AI was an explicit part of Accenture’s 11,000-person reduction. Lufthansa announced plans to eliminate 4,000 jobs in the coming years thanks to AI, and Goldman Sachs is piloting Devin, an AI agent that will automate software engineering, which doesn’t bode well for the 12,000 human engineers currently doing that work. […]

[Bobsled cofounder Joshua] Neckes sees AI as a total workforce reset. “Our economy has a decent percentage of fake jobs that barely had a reason to exist in the first place. There’s just no reason to deal with the headache of having young employees who frequently do the wrong thing, who frequently, you know, take up time and space.” I asked him what Gen Z — the entry-level coders and associate attorneys in those fake jobs — were supposed to do without opportunities. “Be smarter around the new shit and be cheaper,” he says.

This attitude is, unsurprisingly, popular among CEOs. At a Beverly Hills conference last spring, Nvidia CEO Jensen Huang said that “you’re not going to lose your job to an AI, but you’re going to lose your job to someone who uses AI.”

One noticeable absence from all this talk about a labor-market upheaval: Universal basic income. U.B.I. gets a glancing mention in Walsh’s piece as an idea in which there’s been a “new wave of interest” with the advent of A.I. But I’m not sure that’s entirely true: As in the article, U.B.I. seems to barely warrant a mention in the ongoing and inescapable discourse about a (potentially) A.I.-exploded labor market.

This seems particularly odd given how prevalent U.B.I. was as a passion policy in Silicon Valley ten or fifteen years ago. For much of the 2010s, U.B.I. received a lot of attention and energy as a heterodox, futuristic policy occupying a Venn-diagram overlap between wealthy tech-industry libertarians and wonky left-liberals. (Not coincidentally, groups that made up two pillars of the Obama-era Democratic Party.) In 2016, well before hyperscaling turned large language models into the “A.I.” of present-day hype, Sam Altman, then the president of Y Combinator, announced a long-range study of U.B.I. anticipating a “world where technology replaces existing jobs and basic income becomes necessary”; that same year, Elon Musk said he thought a U.B.I. was inevitable given automation to come: “I am not sure what else one would do.” In 2020, Andrew Yang made a U.B.I. proposal called “the Freedom Dividend” the focal point short-lived, tech-coded Democratic primary campaign--probably the high-water mark of the policy’s salience and buzziness.

Strangely, however, amid the rise of L.L.M.s and jobs allegedly lost to A.I. automation--precisely the kind of dynamic that led people like Musk and Altman to call for U.B.I. in the first place--the personalities and pundits who drove interest in the policy through the 2010s seem much less enthusiastic. Altman now prefers to talk about vague, self-derived concepts like “universal basic compute” and “universal extreme wealth,” while Musk has started talking about an ill-defined idea called “universal high wealth.”

Where did all the interest in U.B.I. go? One reason “U.B.I.” and similar cash transfer programs managed to gather so many supporters in the 2010s was that a huge number of policies could be gathered under those concepts. On the right, you could fantasize about eliminating the welfare state entirely and transforming benefits like Medicaid, Medicare, and SNAP into a single monthly check. On the left, guaranteed-income programs have shown enormous promise as targeted ways of alleviating poverty or improving maternal and child health outcomes.

But for the wealthy California libertarians of Silicon Valley, U.B.I. really emerged out of the strong consensus belief that the transformative effects of technology would automate jobs out of existence and shut the resultant unemployed mass off from the wealth otherwise being created by the 21st century economy. Though few of them would say so explicitly, “U.B.I.” in this vision was a pittance offered to stabilize and quiet a permanent underclass.

A given U.B.I. might still be a pittance--offered by libertarians in lieu of comprehensive state welfare program--but the jobless future hazily envisioned by people like Musk was never going to come to pass. In the long run, productivity-enhancing labor-automating technology doesn’t eliminate jobs; nor, for that matter, does it create them. The effect of such technology on the labor market is less a question of “automation” as such and more a question of how it affects the balance of power between labor and capital. To the extent that the threat of automation is a point of leverage in class warfare, it can lower the wages of workers and otherwise disempowering them--as the Gen Z employees from Walsh’s article are finding.

In this way, guaranteed-income programs should be seen not as complementary to “A.I. automation” but as leverage for the other side--workers, who can more easily withhold their labor and otherwise refuse disempowerment if they know they have an income floor. (So long, importantly, as the guaranteed income is provisioned in addition to standard welfare programs, rather than as a replacement.) Altman’s own research has shown this in an interesting way: A three-year OpenResearch study in which 1,000 people were given $1,000 a month found that the main long-term change among subjects was that people worked one fewer week a year, on average.

This was not really seen as a salutary benefit to the investors and executives of Silicon Valley, who worried that the results were proof that guaranteed income would make people lazy and unmotivated to work. But to me, it seems like a sign of unqualified success: The way I read it, the people in the study weren’t “unmotivated” to work that extra week a year, they were simply no longer sufficiently motivated by the wages being offered. If you want to get them working, come back to the negotiating table and pay them more money. U.B.I. in this sense isn’t the runner-up prize for those left behind by automation, the way it often seemed to be regarded by your Silicon-Valley billionaires in the 2010s; it’s a way for workers to empower themselves relative to their would-be bosses. No wonder Altman and Musk don’t talk about it anymore.