On some great and glorious day the plain folks of the land will reach their heart’s desire at last, and the White House will be adorned by a downright moron.

| H.L. Mencken (1920)

…

One hundred years later, Mencken’s prophecy has been borne out.

While we have to concede that Trump has a ‘feral genius’1 for turning grievance into a political movement (like other authoritarian populists), and thereby getting himself elected, he’s clearly out of his depth when trying to actually steer the nation in a positive direction, to put it mildly. Less mildly, he’s a ‘downright moron’, which he has demonstrated over and over again: the tariffs, ICE, gerrymandering, antagonizing our allies and trading partners, and most notably, an absolutely unnecessary war with Iran that will cost us $100 billion at the minimum, with absolutely none of the supposed war aims met.

And, to top it off, the ludicrous UFC fights staged on the White House lawn, yesterday. I couldn’t even bring myself to hate-watch it.

Everyone Hates Data Centers, But Isn’t AI the Real Culprit?

It seems that every day, I encounter another story about growing opposition to data centers, ranging from citizens shouting at their elected local officials at town halls, to states barring their construction after dozens or hundreds have already been built.

To me, though, that’s akin to blaming sewing machines for the fast fashion trend. Yes, sewing machines are employed to make all those cheap, and unsustainable clothes, but the root cause are the businesses that have souped up supply chains to smother the world in a glut of throwaway clothing.

Shouldn’t our anger and opposition be directed to the tech companies contracting for all this computing power, instead of the buildings housing the bazillion server racks that AI requires?

Tressie McMillan Cottom wrote about data center hatred2, recently [emphasis mine]:

Americans hate data centers. They really, really hate them.

A Gallup poll from May found that 71 percent of Americans would oppose a data center being built in their area. In rural communities in Utah and North Carolina, regular people are organizing to stop data center construction, speaking out at public hearings and pressuring politicians for bans. They are passionate enough to attend political education sessions about water rights, land use and thermodynamics. Cities like Tulsa, Okla.; Birmingham, Ala.; and New Orleans have recently passed temporary moratoriums on data center construction. Last week, lawmakers in New York passed a statewide pause on large-scale data centers; other states, including Maryland and Michigan, could be next.

According to polling by Heatmap News, more than half of all Americans support a national ban on data centers. The public seems to agree that data centers are giant, ugly, noisy, smelly altars to industrial-scale hostile architecture. In our virulently partisan country, this constitutes a rare show of consensus.

She goes on to make an impassioned case for the Democrats mobilizing this anger as a central aspect of their platform. She cites some Democrats efforts versus data centers:

Senator Elizabeth Warren has made a proposal that focuses on taxation of A.I. firms and mandating transparency about how the A.I. boom is shaping companies’ financial risks. All of these are good-faith attempts to respond to voters’ anger, but Warren’s message is too wonky to match the moment.

Senator Bernie Sanders has gone further, floating a big idea that’s consistent with his brand of democratic socialism. He called for a national data center moratorium and labor protections for workers displaced by A.I., and he is proposing the “American A.I. Sovereign Wealth Fund Act” to give the American public shared ownership, and therefore control, over A.I.’s expansion and its profits. But, Alex Hanna, director of the Distributed A.I. Research Institute, told me that a wealth fund act would enshrine the tech sector’s as-yet-unproven claims of its importance. This is the risk of treating A.I. as something that is as important as humans discovering fire and inventing the wheel. That’s zealotry. It has no place at a tent revival.

Representatives Alexandria Ocasio-Cortez of New York and Ro Khanna of California are going after data centers with an organizer’s flair for spectacle and an anti-oligarchy message. Khanna has called data centers extractive and uses them as justification for his proposed wealth tax.

This all feels like a rear-guard action to me. Apparently, the Democrats have ceded the high-ground of AI’s inevitability to the Tech Overlords. She spells that out, to some degree:

Data center infrastructure is a marriage of the technology and energy sectors. Separately, the two industries are economic powerhouses; united, they are a behemoth. A.I. interests are well on their way to spending hundreds of millions of dollars on state and federal elections in this midterm cycle, when there are far too few competitive races to influence. The A.I. industry’s deep pockets are making candidates on the left and the right cagey.

Important, too, is the seductive cultural narrative that flows from the pro-data center camp. A powerful bench of celebrity C.E.O.s, exuberant financiers, developers and futurists consistently present artificial intelligence as an inevitable technology Americans must adopt, lest they be left behind. If you accept the inevitability thesis, you are likely to believe that data centers are necessary and public dissent is naïve or, worse, un-American.

To which I say fuck them, and fuck that shit. Instead of bracing for lifelong membership in Jasmine Sun’s ‘permanent underclass’, or tinkering around the edges with anti-data center protests, we should demand AI regulation so that jobs are not lost in order to make billionaires richer.

China — of all places — is leading in this fight, as reported3 by Catie Edmondson:

When a Chinese court ruled late last month that a tech company had illegally laid off a worker after replacing him with artificial intelligence software, it delivered an implicit warning to other employers.==

“The development of artificial intelligence technology should be applied to liberating labor, promoting employment and improving people’s livelihood,” the Hangzhou Intermediate People’s Court wrote. “Labor law allows employers to undertake technological changes and upgrade their operations, but it should also take into account the protection of workers’ legitimate rights and interests.4

The case — the third time the Chinese government has highlighted a ruling siding with workers displaced by A.I. — underscores how Beijing is contending with the need to balance its ambitions for the widespread use of A.I. with the unemployment that might accompany it.

China has invested billions to become an artificial intelligence superpower and raced to integrate the technology across a broad range of industries. But those aspirations have run headlong into a growing political problem: anxiety over the workers who could be displaced by the realization of Beijing’s technological drive.

This issue is singularly acute for China, where more than 200 million workers are stuck in gig economy work, with a weaker safety net than in the US. Youth unemployment is 17% there, and growing. Instead of considering universal basic income — as is being discussed in South Korea, Japan, and the UK — China’s courts are taking a hard line on employers: you can deploy AI, but don’t use it to cut jobs.

Again, Edmondson:

The three court rulings have offered an early glimpse of what that response might look like. In each case, the court said employers remained responsible for keeping workers on the payroll, even if A.I. had rendered their jobs redundant. Judges have repeatedly ruled that replacing workers with A.I. is voluntary cost-cutting that does not justify mass layoffs.

Chinese policymakers appear eager for both workers and employers to get the message. The Hangzhou ruling in favor of the tech worker replaced by A.I. was given a special designation signaling that it should serve as a model for future cases.

In that case, an employee identified in filings only by the pseudonym Zhou had worked as a quality assurance supervisor at an A.I. company until the technology replaced him. When the company offered him a new role that would cut his salary to 15,000 renminbi per month from 25,000, he refused and was fired. The court ruled his employer had failed to properly accommodate him.

We should emulate China, as soon as is possible.

In earlier eras, US unions fought for similar resolution of job-killing technological advance. For example, the International Typographical Union (ITU) was part of the Columbia Typographical Union (CTU) which at its peak had over 120,000 members.

In 1974, the [Washington] Post had about 1,000 printers on the payroll, working some 700 “situations.” But another revolution in printing was taking place and the Linotype machines and the jobs involving hands-on contact with pieces of type begin to disappear.

With some sections already converted from “hot metal,” Post CTU members in 1974 signed their first contract to include a “lifetime job guarantee” that recognized the inevitable disappearance of their craft.

Decades later, only a few hundred ‘printers’ remained, having made the transition from Linotype to cut-and-paste compositing and photography, and then to computer layout software.

But that approach allowed a social transition without dumping 100,000s of ‘printers’ onto the streets. Somewhere between that union-led generational retreat, and Chinese judicial policy to hold onto all jobs threatened by AI, is a human-first answer to the looming AI jobs apocalypse.

If we leave it to the Tech Bros and the corporate finance corps, millions might be laid off over the next decade. We need more time — more breathing room — and a better response than is being offered by even the most left-wing progressives.

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Short Takes

Brace yourself for bad news.

In The Kobeissi Letter (@KobeissiLetter on X) June 14, 2026 we learn some bad news:

Americans can’t find jobs.

The number of Americans not in the labor force who currently want a job rose +76,000 in May, to 6.2 million, the 3rd-highest since July 2021.

These are people who are not officially part of the labor force, meaning they are not actively looking for work, but say they want a job.

This marks the 4th consecutive monthly increase, totaling +349,000.

Since March 2023, this figure has surged by +1.2 million people and is now above 2008 Financial Crisis levels.

As a % of total employment, this metric is up to 3.8%, the 2nd-highest since October 2021.

By comparison, the 2001 recession and the 2008 peaks were 3.6% and 4.3%.

Labor market conditions are deteriorating beneath the surface.

Meanwhile, our federal government is firing workers, closing agencies, and cancelling Joe Biden’s efforts toward industrial policy.

We are on a sharply downward trend.

…

What about bringing back manufacturing jobs?

Back in January, David Uberti looked at factory jobs in the US:

The manufacturing boom President Trump promised would usher in a golden age for America is going in reverse. After years of economic interventions by the Trump and Biden administrations, fewer Americans work in manufacturing than any point since the pandemic ended.

Manufacturers shed workers in each of the eight months after Trump unveiled “Liberation Day” tariffs, according to federal figures, extending a contraction that has seen more than 200,000 roles disappear since 2023.

An index of factory activity tracked by the Institute for Supply Management shrunk in 26 straight months through December, but showed a January uptick in new orders and production that surprised analysts. The Census Bureau estimates that manufacturing construction spending, which surged with Biden-era funding for chips and renewable energy, fell in each of Trump’s first nine months in office.

This is one part of a larger trend: a decline in blue-collar jobs:

It’s not a pretty picture.

…

Young people can’t get started.

Molly Jong-Fast was writing about commencement speakers being booed5 when they waxed lyrical about the wondrous future of AI, but she dropped some stats, too:

Young people are facing what M.I.T. Technology Review calls a “ looming crisis in entry-level work,” and college, once assumed to be a prerequisite for a secure job, no longer feels worth it. The general gestalt coming from a certain sliver of affluent Americans is that college graduates are more liberal trouble than they’re worth and perhaps could be replaced by bots. Marc Andreessen, the venture capitalist and G.O.P. megadonor, mused to Joe Rogan that a bot “never gets drunk, never gets sick, never gets high” and “never files H.R. complaints.” (It never boos a smug commencement speaker, either.)

According to a recent working paper from researchers at Harvard, hiring for entry-level roles at companies that have adopted generative A.I. has dropped each quarter since 2023. What is not clear is whether A.I. is taking people’s jobs or if companies are using A.I. as an excuse for not hiring. Either way, A.I. is not exactly popular with people entering the work force for the first time.

Time to smash the looms?

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I want to be the owner of my own trouble.

| Louise Bourgeois

…

Bourgeois’ quote reminded me of the distinction between positive and negative liberty, as delineated by Isaiah Berlin.

There are supporters of “negative” liberty, best defined as freedom not to be interfered with. Negative liberties ensure that no person can seize his neighbour’s property by force or that there are no legal restrictions on speech. Then there are backers of “positive” liberty, which empowers individuals to pursue fulfilling, autonomous lives—even when doing so requires interference. Positive liberty might arise when the state educates its citizens. It might even lead the government to ban harmful products, such as usurious loans (for what truly free individual would choose them?).

| The Economist, Berlin, Rawls and Nozick

I suppose Bourgeois’ wish is an example — perhaps a shining example — of the overlap of negative and positive liberty: the freedom to be unmolested while pursuing a ‘fulfilling, autonomous’ life.

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Short Takes

Employer concentration is an enormous social ill.

Large corporations are both keeping their low-wage employees at or below the poverty line, and playing the American public as suckers, since our taxes are diverted to provide a social safety net for them, as Michael Sainato reports:

Many workers at some of the largest US corporations have no choice but to rely on healthcare and food assistance because of low wages, even as CEO compensation continues to grow, according to a new report released Wednesday [March 04, 2026].

The report, published by the Institute of Policy Studies, focuses on 20 of the S&P 500 corporations that have primarily US-based workforces and report the lowest median wages of the group.

Collectively, this “Low-Wage 20” employs 6.7 million people in the US. The median pay at a majority (75%) of the companies is lower than the income minimum for a family of three to be eligible for Medicaid in most states. At 13 of the companies, median pay was also lower than the Supplemental Nutrition Assistance Program income threshold for a family of three.

Nearly a quarter of Walmart employees (29.3%) and half of Amazon workers (48.4%) in Nevada – which collects Medicaid enrollment numbers among employees at large companies – were on Medicaid in 2024, according to the report.

These corporations should be regulated to pay a living wage. We should raise minimum wages, and impose additional regulations and taxes on giant corporations acting as cartels to immiserate the most powerless. More links in the footer.

…

ChatGPT Health.

ChatGPT Health regularly misses the need for medical urgent care and frequently fails to detect suicidal ideation, a study of the AI platform has found, which experts worry could “feasibly lead to unnecessary harm and death”.

OpenAI launched the “Health” feature of ChatGPT to limited audiences in January, which it promotes as a way for users to “securely connect medical records and wellness apps” to generate health advice and responses. More than 40 million people reportedly ask ChatGPT for health-related advice every day.

The first independent safety evaluation of ChatGPT Health, published in the February edition of the journal Nature Medicine, found it under-triaged more than half of the cases presented to it.

| Melissa Davey, ‘Unbelievably dangerous’: experts sound alarm after ChatGPT Health fails to recognise medical emergencies

Isn’t this one of the areas where LLMs were supposed to excel?

…

Speaking of health care.

Jena McGregor reports that some young, healthy workers are opting out of employer health-care plans:

Some 61% of workers who have the option to enroll in a company health plan did so in 2025, down from 64% in 2020, according to health policy organization KFF.

Workers dropping employer-based health insurance cite rising costs, and experts warn employers may see health-care costs rise if plans lose too many young, healthy members.

Economists warned this would happen as health care costs continue to rise, even for those with employer-provided plans. If we had universal healthcare this would not be an issue, note.

…

The case for year-round daylight saving time.

Staying on daylight saving time year-round would prevent an estimated 36,550 collisions between deer and vehicles, whereas staying on standard time would add 73,660 of these collisions every year — a difference of more than 100,000. The human toll of staying on standard time would also be significant: Compared with year-round daylight saving time, year-round standard time would cause 100 more deaths, 6,000 more injuries and at least $3.5 billion in costs every year through increased deer-vehicle collisions alone.

Of course, having more crashes with deer is far from the only cost of standard time. The number of fatal traffic accidents at night — caused by deer or anything else — is three times as high as it is during the day, and in the dark the risk of pedestrian accidents is up to seven times as high. Permanent daylight saving time would prevent 366 fatal pedestrian and vehicle accidents a year with the help of brighter evenings during the four and a half months of the year we currently spend on standard time. Conversely, staying on standard time for an extra 7.5 months each year would add about 610 fatalities — a difference of nearly 1,000 human lives.

| Laura Prugh

Year-round standard time shouldn’t even be considered.

…

Got milk?

More than 750,000 immigrants left the U.S. labor force during the first half of 2025, according to the Pew Research Center, creating a growing challenge for industries that rely heavily on those workers. Dairy farming is near the top of that list: Immigrants make up more than half of that sector’s labor force.

Another administration could have promised that shifting away from immigrant labor would deliver real benefits without misleading Americans about the nature of those benefits. It could have sought to help family farms — for example, by providing low-cost financing for automation. It could have dealt openly and fairly with immigrants who will continue to milk many of the nation’s cows for years to come.

| Binyamin Appelbaum, 2026-02-09 Trump Wants More Jobs for Americans. He’s Getting More Robots Instead.

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I’d woken early, and I took a long time getting ready to exist.

| Fernando Pessoa

…

Since my son Conrad and daughter-in-law Lydia had a new baby (Killian) in September, I have a new role in life: walking their dog when Conrad drops him off around 6 am, Monday through Friday.

This has a few benefits. One, I take a walk in the morning light (at least now that winter is over) and gently mull over thoughts before I sit in front of a screen. Second, this has led me to go to bed an hour or so earlier and get a longer rest. Third, because I am obliged to take the walk, once Rocky and I return, I am already a few thousand steps toward my daily step goal.

I often think about Pessoa’s quote when making that walk, and when 7 am rolls around, and I sit down at my desk with a cup of coffee, I am ready to exist.

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AI is unraveling the social fabric of work.

Aki Ito, who had become one of my favorite writers, has written The antisocial workplace1, and I pulled the lede as the title of this section, although she — or her editor — buried it like seven paragraphs in:

AI is unraveling the social fabric of work.

She uses a marketing director, Daniel Duceuster, as a lens into how AI is attenuating human interaction in the workplace:

Deceuster is early to recognize a profound shift underway as AI tools permeate corporate America [he said he is interacting 50% less with coworkers]. “People are increasingly choosing to work alone,” says Jessica Reif, an incoming professor of management at Wharton who’s been studying AI’s effects on teamwork.

Signs of strain are already emerging. In January, Cisco found that its employees who were the most active AI users trusted their teams less than intermittent users, likely because the power users were spending more time on their own and less time with their colleagues. “AI can unintentionally create isolation,” the company concluded, “when it’s adopted individually rather than collectively.” The coaching platform BetterUp found that some workers are turning to AI for the kind of feedback they used to seek from mentors and managers. Those employees tended to report lower levels of team coordination, along with higher rates of burnout and a greater desire to leave their jobs.

Less contact and socialization with others can lead to a fragmentation of the social glue holding things together:

“If we aren’t thoughtful about this, we risk turning work into something that feels more isolated and atomized,” Reif tells me. “We’ll just be combining our inputs in a way that feels more like an assembly line than a vibrant workplace.”

[…]

If the previous office tools made it easier for colleagues to connect, AI seems to be replacing those connections altogether. “ChatGPT and tools like it are giving us this alternative way to accumulate knowledge that would otherwise be shared interpersonally,” Reif tells me. “It gives people this option of opting out.”

Pre-AI collaboration tools have led to over-communication and overwhelm. Now AI shows up, and users may adopt it to reduce the overhead and friction of collaboration.

Even Ito started to opt out herself, relying on ChatGPT instead of interacting extensively with her editor, Zak.

For a while, I was pleased with my lower-friction ways. But as I reported out this story, I started to wonder what I might be losing in my quest to bother Zak less. I was certainly talking to him less. Was I missing out on opportunities to learn from him? Was I losing my ability to navigate disagreements? Did I feel less close to him? I wondered what being less needy was doing to the most important professional relationship I have — and what that meant for how I ultimately felt about my job.

Collaboration overwhelm is a real thing. But are they throwing out the baby with the bathwater?

The small interactions that our jobs previously forced us to have were what made teams work well together — often without anyone realizing it. They built the goodwill colleagues need to navigate the disagreements that inevitably come up.

[…]

People will still need to coordinate effectively and trust each other — even if their day-to-day work becomes more solitary.

Ito quotes some others who are trying to balance LLM use with social ties, so that the benefits -- like strategic alignment don’t get lost as everyone is talking to the LLM agents, and critical insights never get shared.

The challenge for all of us will be to juggle these new tradeoffs: the immediate productivity benefits of a less interdependent workplace, alongside our need for teams that work well together and jobs that still give us a sense of connection.

I think this personalization of the social impacts of AI is just wrong, much like exhorting individuals to become more resilient in the face of the pandemic or other exogenous forces. Ito does point her finger at the companies:

That’s why it’s ultimately up to our companies — and the people who are redesigning the way work gets done inside them — to figure out systematic ways to preserve the social aspects of our jobs.

And maybe our governments, as well. Regulations to slow or stop the alienation (or replacement) of people by AI could be crucial, but never mentioned. She contrasts the pandemic and remote work upending everything: on one side, post-COVID, some companies forced everyone back to the office, while others retained hybrid/remote work and emulated face-to-face interactions. She also compares the blowback on screens in schools (which is the closest she comes to discussing government stepping in).

How long will it take for our workplaces to figure out how to benefit from AI’s productivity boosts without driving us away from each other? “We don’t even know what we’ve unleashed yet,” says Deceuster, “or how to effectively use it.”

Which is a good reason to slow down.

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Week In Review

The Anti-Social Century

Aki Ito referenced Derek Thompson’s The Anti-Social Century, which draws on Robert Putnam and Eric Klinenberg‘s work detailing how lonely and alone Americans are, but even without bowling leagues and rotary meetings,

we still go to work. Even as all those other communal institutions withered away, work kept bringing us together with other people. If we lose even that to AI, we’ll become more efficient than we’ve ever been — and more alone, too.

…

Soft and Softer

I wrote about the new memes of ‘soft off’ and ‘soft on’ days, where people pretend to be working or work at a slower pace, respectively:

I wrote

My hunch is people are building the four-day workweek organically and bottom-up, since their employers aren’t smart enough to institute it as top-down policy.

…

Gaslighting, not career advice

In Suspended Terror,

the main section was about women being gaslighted, and I gathered insights from Ephrat Livni, Tressie McMillan Cottom, and Jessica Grose. An excerpt:

The obstacles that come with working in a sexist culture are beyond any individual’s control. And so advocating a do-it-yourself approach to on-the-job equality may actually be a kind of gaslighting—just one more way for institutions to deflect blame and make women question themselves and doubt their sanity. It’s the society we operate in that needs fixing, not how we ask for money, the tone of our voices, or our outfits.

| Ephrat Livni

Livni’s referenced article, All career advice for women is a form of gaslighting, really says it all.

…

Over at Workings.co

This is really for Obsidian nerds. I wrote

Workings

First Look: Sync Embeds Plugin

I came across the new sync embeds plugin recently. From the repo…

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11 days ago · 1 like · Stowe Boyd

where I explore a new plugin and how I use it in my workings.

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I encountered two complementary terms that are making the social rounds on LinkedIn, TikTok, IG, and Reddit. They share the root word ‘soft’, in distinction with ‘hard’. (Duh).

Soft-Off Day, according to Kara Reinhardt at LinkedIn:

The trend of "soft off days" — where employees engage in personal activities during work hours — has surged as many seek better work-life balance, Fast Company reports. The practice often stems from feeling underpaid and overworked, prompting workers to reclaim their time. Employees typically manage their workloads and monitor their messages to maintain the appearance of productivity. A growing acceptance and lack of guilt suggests a need for workplace cultures that prioritize flexibility and employee well-being.

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The Soft-On Day is a bit more work-focused: instead of indulging in personal activities while on the clock, you continue working at a slower, less aggressive pace. Andrea Navarro links this variant of work/life balance productivity to TikTok creator Sloane (@sloane_wfh) [emphasis Navarro’s]:

According to Sloane, a soft-on day is a day “when you spend the day catching up on all the little things that you’ve been needing to get done.” She claims you “have to do it from your couch, in your cozies, while having your favorite re-runs on in the background.” This is a day when you’re online and getting things done, just at a lighter, lower-stress pace. So you’re available, you’re responsive, and you’re chipping away at the tasks that don’t require deep focus, but you’re not pushing yourself to operate at maximum productivity.

[…]

Her premise is simple: every WFH employee should have at least one soft-on day a week—and she’s not the only one who thinks so. Users in the comments of her videos agree, claiming soft-on days are “mandatory.” Some even say they take up to three soft-on days every week to maintain their sanity and productivity output.

I personally interpret this trend as a presaging of shorter workweeks. There’s growing evidence that workers can get the same amount of work done in four days as in five. See Juliet Schorr’s Four Days A Week, for data-driven case studies and meta-analysis of other research, or listen to her TED talk.

Although her work predates the soft trend, my hunch is people are building the four-day workweek organically and bottom-up, since their employers aren’t smart enough to institute it as top-down policy.

Have you taken soft days, of either flavor? (I’ve made this a free post so everyone can answer the question.)

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People can live in suspended terror for only so long.

| Tressie McMillan Cottom

…

I didn’t provide a citation for Cottom’s quote above because I will be exploring her related thoughts, especially regarding influencers' advice to women to embrace AI as part of a bruising scramble up the corporate jungle gym.

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Will The Gaslighting Never End?

In All career advice for women is a form of gaslighting, Ephrat Livni, back in 2018 in the beforetimes, tore into the double and triple binds that suffocate women in the workplace, and the lies that animate the struggle for work justice in our time:

If you’re a working woman, you’ve likely been inundated with advice about how to ensure that gender double standards don’t impede your brilliant career. Assert yourself boldly at meetings in an appropriately low tone of voice, yet purr pleasingly when negotiating salary. Be smart but never superior, a team player though not a pushover, ever-effective yet not intimidatingly intellectual. Calibrate ambition correctly, so that none are offended by your sense of self-worth, but all seek to reward your value. Dress the part.

Inevitably, even in the most allegedly enlightened workplaces, women contend with subtle biases. And so the fairer sex gets the message that we can’t just work. We must also contort and twist and try not to seem bitchy as we lean in.

But the obstacles that come with working in a sexist culture are beyond any individual’s control. And so advocating a do-it-yourself approach to on-the-job equality may actually be a kind of gaslighting—just one more way for institutions to deflect blame and make women question themselves and doubt their sanity. It’s the society we operate in that needs fixing, not how we ask for money, the tone of our voices, or our outfits.

Here, in 2026, nothing much has changed for the better. In a political climate where DEI is being erased by corporations willing to bow down to political pressure, and where capable senior military officers are pushed from promotion lists because of their sex or skin color, things have only gotten worse.

But that hasn’t slowed the selling of advice about getting ahead. Cottom1 writes about influencers who have now taken to promoting AI as the fast path to being a ‘girl boss’: a term now updated for our time, to go beyond just leaning in. Cottom writes about Emma Grede, who seems the Cruella De Vil of women whisperers [emphasis mine]:

Emma Grede is not a household name, but her literary debut (a self-help “leadership” book) tells a similar tale. The book itself has the hallmarks of the confessional tell-all advice genre that once sent women corporate leaders into the public domain. Grede calls herself a “three-hour mum” because she sees her four children three hours on Saturday and Sunday — 9 a.m. to noon — and she said she believed that working from home is “career suicide” for women who want it all. It’s “Lean In” on steroids. Unsurprisingly, her perspective courted its own outrage, from an audience that knows how hypervisibility, ambition and work obsession is fanfic for a corporate workplace that penalizes women whether they are visible or invisible, ambitious or checked out.

Gaslighting, again.

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Cottom places this ‘Lean In’ on steroids firmly in 2026, and asks the right question:

The girl boss leadership strategy isn’t just outdated; the “how to get ahead” genre is the antithesis of today’s labor market. Getting ahead is for a time when companies are hiring. The A.I. economy we are building promises that companies will be able to make profits without making career paths. That’s the entire selling point.

So how are you going to claw your way to the top of a pyramid that has no middle?

She points out that the influencers like Grede are liars; they

promised us that in a scary world all we needed was a little bit more money to be less afraid. That message belies the truth that women can see with their own eyes. Once, women bought into their message. They earned educational credentials only to be told that they shut men out of schooling. They delayed child bearing to start competitive careers; now their political leaders are telling them that they’re failing at making enough babies. They started businesses and brands and built side hustles; now they’re being told that they did not do it enough or the right way or for the right people.

Women are facing an economic apocalypse.

The old Obama-era platitudes — that empowerment would bring more justice in the workplace — are just laughable now. Cottom points out that Democrats have no answer to her question, and Republicans want women out of the workforce, having children.

Jessica Grose points out that Republicans are calling for a return to higher teen pregnancies, even though older pregnancies have risen:

There’s been an increase in births by college-educated mothers, while births by women without high school diplomas have decreased and women with college educations are more likely to be working than those with less education.

But some conservatives blame women in the workforce as the culprit in this shift toward older pregnancies, rather than a sensible response to market forces. Two partners need two jobs to pay the rent, right?

And Grose notes men are likewise doing more to help in child rearing:

Ariel Binder looked at data from the American Time Use Survey and found that after the Covid-19 pandemic, husbands reduced their paid work time and increased their housework time.

[…]

The dynamic of more housework and less paid work was more pronounced among college-educated men and men with young children. Binder notes that this is a reversal of previous trends, where for decades, women increased working hours and reduced time spent on housework, but men’s behavior remained fairly static.

So, college-educated women continue to push for it all, which translates to later pregnancies — allowing them to dedicate time to work advancement, or at least survival — as well as men finally stepping up to take on more housework, a long-overdue adjustment.

I’ll leave the final word to Grose:

Maybe, instead of yelling at young men and women for making the wrong choices, we should be listening to them talk about how they want to live, and try to figure out the kind of society that would best support them.

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When you think of it, life is an assembly of creative mistakes.

| Roger Rosenblatt, I Ain't Dead Yet

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Embrace Mistakes or Abandon Hope

When I read Rosenblatt’s recent column, I was reminded of the insights offered by James Bareham in The essential art of making mistakes:

One of the best lessons I learned early on in my creative career was how important it was to not worry about making mistakes; better to embrace them. Not just from the perspective of trial and error to improve my skill set, but sometimes the errors I made were better than any of the original ideas in my head. Making mistakes is being creative.

He clarifies later in the piece:

Making mistakes is my definition of learning, an intrinsic part of the creative process.

What we are wired to do is to learn, and underlying creativity is learning by making mistakes: trying experiments which only once in a while work out. Being creative requires accepting that we can’t know in advance what will work and what won’t. And one part of creativity is to sift out the good mistakes, and use them, like a starter for sourdough.

Bareham intended his piece as a polemic against AI as being inherently uncreative:

GenAI isn’t a genius author channeling their neon imagination through psychedelics; it’s a statistician with a spreadsheet. GenAI is designed to fit the brief to the letter, and any mistakes aren’t “happy accidents” (to borrow the classic Bob Ross phrase) so much as they are muddled, discomforting negative side effects that have become something of a watermark for these generative models. I shouldn’t be surprised that everything that comes out is so metaphorically beige.

The problem with AI is that it makes too many bad mistakes and not good ones.

And when you are working at being creative, a ‘statistician with a spreadsheet’ might not be the best collaborator or muse.

Remember that thinking creatively leads to hope, as Solitaire Townsend pointed out:

This research was shared in 2023 and has played on my mind ever since. Based on a global survey of nearly 2,300 people, the behavioural economists at BEworks discovered that creative thinking isn’t just about making art or telling stories, it’s a way of seeing and shaping the world that naturally leads to hope and action.

In fact, creative people in the study were more likely to believe in humanity’s ability to tackle the climate crisis, to feel personally motivated, and to put effort into sustainable behaviors.

So, don’t outsource your creativity to AI chatbots: you may also inadvertently outsource your hope.

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Week in Review

This last week I published a few interesting bits:

..

I had promised to post something about the renewed interest — and backlash — about ‘Girl Bosses’: it’s in the works.

…

Real income growth down.

Mike Zaccardi shared this dismal news from Goldman Sachs:

Real personal income per worker excluding transfers declined 0.6% over the last year, a pace rarely seen outside of recession.

Uh-oh.

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Capital beating Labor.

Via Kevin J. Delaney [emphasis mine]:

In the first quarter of 2026, labor’s share of gross domestic income fell to 51%, the lowest level on record, according to a government report. Since 2019, wages have grown by 3% when adjusting for inflation, while corporate profits have increased by 50%.

Note that the Goldman Sachs numbers real income growth dropped by 0.6% last year.

…

Hiring is hard to do.

Richard Thaler, the Nobel laureate in economics, shared this insight on hiring [emphasis mine]:

Hiring decisions are difficult in general, and getting it right becomes harder as you move up the organizational hierarchy. The most reliable predictions about job performance come from what are essentially tests. If you are hiring a chef, ask her to cook something. Predicting whether she can also keep everyone in a large restaurant working together is harder. What test can you give to measure that ability?

In the absence of a suitable proxy for observing someone doing the actual job, many employers resort to some sort of interview. This is problematic, because unstructured interviews provide surprisingly little useful information about future job performance.

One illustration of how hard it is to pick and evaluate successful leaders comes from the dismal record of hiring head coaches in major sports. This past year, nine of the 32 National Football League teams fired their head coaches, and a 10th resigned. All these coaches had gone through rigorous selection processes and had track records. Yet the turnover rate was more than 30 percent in a single year.

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For decades, business leaders have placed innovation as a top priority for business -- if not the top priority. However, they struggle to find people with the skills to innovate.

It hardly needs to be said that innovation requires creativity, transforming existing knowledge, ideas, or objects into something novel and interest…

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Tech is, to put it bluntly, full of people lying to themselves. As countless cult leaders, multilevel marketing recruits, and CrossFit coaches know, one powerful way to convince people that following you will change their life is to first convince yourself.

| Christopher Mims, What I Got Wrong in a Decade of Predicting the Future of Tech

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A Parade of Pundits

Mims wrote the above in the Wall Street Journal in May 2024, as a mea culpa, reflecting on ‘a decade of embarrassing myself in public—and having the privilege of getting an earful about it from readers’.1

His point no. 1 was: ‘disruption is overrated. The most-worshiped idol in all of tech—the notion that any sufficiently nimble upstart can defeat bigger, slower, sclerotic competitors—has proved to be a false one.’

He goes on to credit Jill Lepore for her magisterial debunking of Clay Christensen’s ‘disruption theory’, in which — along with many other observations — she shows why Christensen’s model fails:

Disruptive innovation as a theory of change is meant to serve both as a chronicle of the past (this has happened) and as a model for the future (it will keep happening). The strength of a prediction made from a model depends on the quality of the historical evidence and on the reliability of the methods used to gather and interpret it. Historical analysis proceeds from certain conditions regarding proof. None of these conditions have been met.2

A pragmatic insight is that, in 2007, Christensen and his model predicted the iPhone's failure, which went on to generate 150 billion dollars in revenue in just the next five years and has now generated trillions.

…

But Christensen and disruption theory are not the sole cultish pundits and myths out there, as Jerry Neumann recently laid out in Startup Punditry’s 25 Years of Failure3. Neumann uses an analytic framework similar to Lepore’s in a broadly sweeping condemnation of start-up punditry. However, his argument lies on a stark point of fact: if these pundits — ranging from Michael Porter, Steve Blank, Eric Ries, and others — were offering advice that actually helped start-ups thrive, it should show up in the numbers. But it doesn’t:

Neumann levels his critique against the claims of ‘startup science’:

The New Punditry’s advice was, instead, intuitively rational, apparently well-argued, and offered founders a step-by-step process for building a business amid real uncertainty. Steve Blank’s customer development method in The Four Steps to the Epiphany (2005), for example, taught founders to treat their business idea as a set of falsifiable hypotheses: get out of the building, interview potential customers, and validate or kill your assumptions before writing any code. Eric Ries’ The Lean Startup (2011) built on this with the Build-Measure-Learn loop: Launch a minimum viable product, measure real user behavior, and iterate rapidly rather than waste time perfecting a product no one wants. Osterwalder’s Business Model Canvas (2008) gave founders a tool to map the nine key components of a business model and pivot when something isn’t working. Design thinking, popularized by IDEO and Stanford’s d.school, emphasized empathy with end users and rapid prototyping to surface problems early. Saras Sarasvathy’s Effectuation Theory prescribed starting with a founder’s own skills and network rather than reverse-engineering a plan to meet a distant goal.

These pundits were consciously trying to build a science of entrepreneurial success. By 2012, Blank said that the National Science Foundation was calling his customer development framework “the scientific method for entrepreneurship,” and claimed that “we now know how to make startups fail less.” The official Lean Startup website claims that “The Lean Startup provides a scientific approach to creating and managing startups,” and the back cover of his book quotes Tim Brown, CEO of IDEO, saying Ries “proposes a scientific process that can be learnt and replicated.” Meanwhile, Osterwalder claimed in his PhD thesis that his Business Model Canvas is rooted in design science (the precursor to design thinking).

His basic conclusion is ‘if there’s one thing we know about startup punditry, it’s that it hasn’t worked’. The science preached by the pundits seems an illusion, and he wonders why [emphasis his]:

Behind these ideas, it seems inconceivable that they have not made a difference. And yet the data suggests that we have learned precisely nothing.

If we are ever to build a true science of entrepreneurship, we need to understand why. There are three possibilities. First, maybe the theories are simply wrong. Second, maybe the theories are so obvious that formalizing them was pointless. Or third, once everybody uses the same theories, maybe they stop conferring an advantage. Strategy is about doing something different from your competitors, after all.

Neumann sets about bursting all three of those bubbles. Most critically, perhaps, he argues that (a la Karl Popper) ‘a theory is scientific only if it can, in principle, be proven wrong’. Neumann points out that very few have applied this test to entrepreneurial innovation. But pundits aren’t motivated to test if their theories are right: ‘they make money and gain influence by selling books’.

The whole enterprise has the structure of what the physicist Richard Feynman called a “cargo cult science edifice that mimics the form of science without its substance, deriving rules from anecdotes without establishing underlying causality. Just because a handful of successful startups conducted customer interviews does not mean your startup will succeed if you do too.

Once again, this echoes Jill Lepore’s takedown of Christensen:

The handpicked case study, which is Christensen’s method, is a notoriously weak foundation on which to build a theory.

Strangely, Neumann’s essay never mentions Christensen’s disruptive innovation or Jill Lepore’s assertive rejection of its widespread adoption in business.

Lepore more or less sums up with this:

Disruptive innovation is a theory about why businesses fail. It’s not more than that. It doesn’t explain change. It’s not a law of nature. It’s an artifact of history, an idea, forged in time; it’s the manufacture of a moment of upsetting and edgy uncertainty. Transfixed by change, it’s blind to continuity. It makes a very poor prophet.

Pundits are not, then, prophets, and their theories go untested because they have no motivation to actually test them.

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Emergent Discovery

I’ve written about Flagship Pioneering and their approach to innovation in biosciences several times. Noubar Afeyan and Gary P. Pisano published What Evolution Can Teach Us About Innovation4 in 2021. I continue to be surprised how little effect their approach has had outside of Flagship.

You might want to look at these two workfutures.io pieces: Emergent Discovery, or Applying Evolution To Innovation and Innovation: How Management Must Change in an Emergent Discovery Culture offer a good summary, starting with this from the first piece:

Noubar Afeyan and Gary P. Pisano have done us all a great service in describing in detail the techniques and philosophy behind the breakthroughs that Flagship Pioneering — the ‘venture-creation’ firm behind Moderna and 100 other life-sciences businesses — has created in applying Darwinian selection and variation to innovation. This technique is Emergent Discovery.

Unlike the charlatan pundits that Neumann and Lepore deride, emergent discovery is based on natural law: evolution. As the authors spell out:

Many people believe that the process for achieving breakthrough innovations is chaotic, random, and unmanageable. But that view is flawed, the authors argue. Breakthroughs can be systematically generated using a process modeled on the principles that drive evolution in nature: variance generation, which creates a variety of life-forms; and selection pressure to select those that can best survive in a given environment.

Maybe I should become an innovation pundit and write a book on how an emergent discovery approach could revolutionize other industries, not just biosciences?

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It is far easier to make war than peace.

| George Clemenceau

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A Bias Toward Action

Clemenceau is also remembered for saying ‘War is a series of catastrophes that results in a victory’ and ‘War is too serious a matter to entrust to military men’, which suggests that his experience as Prime Minister of France during World War I led him to a deep understanding of the frailties of peace and traps of war.

The top-most quote can be generalized as ‘It is far easier to take action than to think’, a tendency that is increasingly in vogue in today’s AI-accelerated business climate. How many times have I recently read that the AI economy is moving so fast that slower, more deliberative modes of decision-making must be rejected? A lot.

Daniel Kahneman won the Nobel prize in economics for his breakthroughs in behavioral economics, although trained as a psychologist. He, Dan Lovallo, and Olivier Sibony wrote1 about the two systems we use for navigating the world before his masterpiece, Thinking, Fast and Slow, was even released [emphasis mine]:

According to cognitive scientists, there are two modes of thinking, intuitive and reflective. (In recent decades, a lot of psychological research has focused on distinctions between them. Richard Thaler and Cass Sunstein popularized it in their book, Nudge.) In intuitive, or System One, thinking, impressions, associations, feelings, intentions, and preparations for action flow effortlessly. System One produces a constant representation of the world around us and allows us to do things like walk, avoid obstacles, and contemplate something else all at the same time. We’re usually in this mode when we brush our teeth, banter with friends, or play tennis. We’re not consciously focusing on how to do those things; we just do them.

In contrast, reflective, or System Two, thinking is slow, effortful, and deliberate. This mode is at work when we complete a tax form or learn to drive. Both modes are continuously active, but System Two is typically just monitoring things. It’s mobilized when the stakes are high, when we detect an obvious error, or when rule-based reasoning is required. But most of the time, System One determines our thoughts.

Lovallo and Sibony, in an additional paper, focused specifically on the need to recognize uncertainty as a way to counter the bias toward action, and to think more slowly [emphasis mine]:

Most executives rightly feel a need to take action. However, the actions we take are often prompted by excessive optimism about the future and especially about our own ability to influence it. Ask yourself how many plans you have reviewed that turned out to be based on overly optimistic forecasts of market potential or underestimated competitive responses. When you or your people feel—especially under pressure—an urge to take action and an attractive plan presents itself, chances are good that some elements of overconfidence have tainted it.

To make matters worse, the culture of many organizations suppresses uncertainty and rewards behavior that ignores it. For instance, in most organizations, an executive who projects great confidence in a plan is more likely to get it approved than one who lays out all the risks and uncertainties surrounding it. Seldom do we see confidence as a warning sign—a hint that overconfidence, overoptimism, and other action-oriented biases may be at work.

Superior decision-making processes counteract action-oriented biases by promoting the recognition of uncertainty. For example, it often helps to make a clear and explicit distinction between decision meetings, where leaders should embrace uncertainty while encouraging dissent, and implementation meetings, where it’s time for executives to move forward together.

Looking at the war that the US finds itself in — by overconfidence and a hubristic bias toward action — we can be certain that those who decided to initiate the war on Iran forgot — or never read — Clemenceau’s thoughts on war and peace. And I would be surprised if President Trump or Secretary Hegseth read Thinking, Fast and Slow, or even considered that a bias toward action is dangerous, especially when the stakes are high, and uncertainty rules the day.

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Week In Review

On a personal note.

I had a singularly unproductive week preceding Memorial Day.

Somehow — I’m not exactly sure how — I managed to injure my right thumb. I woke up one morning, Tuesday last, and the base of my thumb ached, as if it had been ‘stubbed’ (as I have sometimes done with my big toe).

After a bit of research, it appears I was suffering from ‘mommy’s thumb’ or DeQuervain's Tendonitis. One reason for that prognosis is that after icing it for a few hours and two days of no typing, the pain had completely stopped, meaning the swollen tendon in my thumb had worked free from the channel it had caught in. Whew. No surgery required.

The second factor in my lack of productivity was something more pernicious: overwhelm. I am an avid notetaker and daybook curator, relying on the Obsidian platform. To avoid a too-detailed explanation, I have been juggling a long list of works-in-process, source materials, and plans for the future. Last week, I reached the point where things became unworkable.

The solution turns out to be conceptually simple but complicated in practice. I had been managing tasks in several Kanban boards, for example, one for workfutures.io. However, I had over a hundred tasks on that one board alone; other boards were overflowing as well. I resolved to create a dozen or so smaller boards for materials, working notes, and plans related to narrower topics — such as ‘AI backlash’ and ‘girl bosses’ — rather than the entirety of everything workfutures.io.

As I said, easy conceptually. But in practice, it took me a few days to retool those hundreds of tasks, sprinkled all across my Obsidian folders, and create the dozen or so topic-centric Kanban boards.

As I was involved in that activity, I also unearthed dozens of old notes and articles related to the often newly identified topics. A sort of housecleaning, beating down the cobwebs, and also decreasing the background stress I’d been feeling for the past months, as the tasks had been mounting.

I feel I can breathe, again. But I didn’t post much last week. Apologies.

What’s coming next.

I am going to try to share some materials I’ve pulled into my notes prior to writing about them in detail.

I am working on a few front-burner topics:

• The term ‘girl boss’ is getting some play, often as a kind of backlash against the Lean In era stereotype, and the excesses of self-help authors. See, for example: Plot Twist newsletter: This self-help book has hit the zeitgeist | The Economist; The Revolt Against the Girl Bosses Has Finally Come | Tressie McMillan Cottom; It’s Not a Mystery Why Fertility Rates Are Declining | Jessica Grose.

• The backlash against AI is mounting. Even Pope Leo has things to say. Graduating seniors are booing tone deaf convocation speakers lauding AI. One survey found that three-quarters of Americans worry AI could pose a threat to humanity. What are the EU and China doing differently than the US? See, for example: China Wants A.I. to Flourish, but Not at the Expense of Jobs | Catie Edmondson; Empowering American Workers in the Age of AI | Bharat Ramamurti; Gov. Gavin Newsom to Sign Executive Order Aimed at A.I. Job Loss | Cecilia Kang; Resistance | Michelle Kim

• Also tracking other themes: employer concentration, paid parental leave; meritocracy; and, of course, bad bosses.

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One useful way to consider alternative approaches to decision-making is through the intersection of two dimensions: the degree of autonomy for the one proposing the decision and the speed of the process to get the decision accepted by those most impacted. That’s where this essay is headed, but first, I’ll lay out the story of how I learned what I now know about decision-making.

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My Story

When I first started in the world of business decades ago, I had formal training only in my discipline -- computer science -- and no management training whatsoever1. And the first few companies I worked for had well-defined decision-making approaches but did not lay them out very clearly. Apparently, I was supposed to learn them by osmosis, on the job.

The thinking then was that there were basically two sorts of decision-making. Senior executives made big decisions autocratically as the head of any organization or sub-organization. That might come after discussions with other executives (and perhaps the board) and subordinates. Alternatively, small decisions were made by individuals—if truly small—or, more generally, by a group or team through consensus.

A few years later, when I became a manager and then president of a software company, Meridian, I still had no formal training in management. As a young leader of a software startup with a background in computer science (and only a few years of experience leading small technical groups), I managed a 25-person company as a few overlapping teams, and largely let the heads of those teams determine how decisions were made in their own domains.

Personally, I was constitutionally disinclined from the most primal of decision-making approaches: autocracy. I didn’t want to make major decisions unilaterally, especially since several team leaders owned more stock than I did. I relied on the team leaders — the head of sales, programming, and operations — to work with me in a model of consensus-oriented decision-making. One of us would propose some company-critical decision — like the merger that we eventually executed with our largest (and publicly-traded) competitor, or taking on a major contract — and if an initial straw poll vote failed to pass unanimously, we’d talk the issues through until we all agreed on the decision and its ramifications. A slow but thorough process. But we, as a group, were confronted only with existential problems; simpler issues were handled by other teams.

The programmers adopted what I would now characterize as a consent approach to decision-making. Consent is an approach to group decision-making that short-circuits the hard work of consensus by limiting objections: members of the group can withhold consent, but only for a well-defined reason. The proposer can counter an objection by amending the proposal and at some point the objector assents. Once all objections are resolved — when all can live with the proposed decision — consent is achieved.

As Ted Rau characterizes it:

Consent is defined as ‘no objection’. Not having an objection is slightly different from agreeing. We refer to that extra space as the range of tolerance. We don’t have to find the overlap of our preferences in order to make a decision. Instead, we seek the overlap of our ranges of tolerances which gives us much more to work with.

It’s strange that I haven’t really learned much new about group decision-making in the decades since running that software company. (If you were waiting for the end of the story, yes, we merged with our largest competitor, and I become head of engineering for a 175-person software company, Verdix, that merged with another firm to form Rational Software, later acquired by IBM.)

However, a few years ago I learned about an approach I hadn’t encountered before. The advice process involves a great deal of autonomy for the decision proposer while retaining a means for collective intelligence to influence the decision. I read about it in 2017, from Richard Bartlett:

Anyone can make any decision, so long as they are willing to take responsibility for the outcome, and they have first listened to input from anyone who will be affected, or who has relevant expertise.

Notice it says listened to, not agreed with. If your relationships are good, this gives you most of the benefits of consensus, at a fraction of the cost.

Radical autonomy! It seems like a short-cut consent approach, with the obligation on the proposer to overcome objections removed. An element of autocracy for everyone.

Bartlett makes the point that the advice process needs to operate in the long run in the context of other organizational feedback cycles, so the responsibility element is analyzed and learned from. I confess I have never worked in an organization using the advice process as a regular, general approach to decision-making, but I am sold on the principles.

Many ideologies have arisen in the intervening years about the relationships between decision-making and organization design — such as Sociocracy, Holacracy, Frederic Laloux’s Teal, and a number of others. For today, though, I am limiting my discussion to the nuts-and-bolts of the decision-making approaches, and their differences.

I think of decision-making at this scale as the mitochondrion of the organization, the organelle in our cells that creates energy. Teal, Holacracy, and other theories of organization are aspirational rather than focused on the nuts-and-bolts, bottoms-up operations of small-group decision-making. I’ll leave larger-scale organizational forms as a topic for a later day.

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Comparing The Approaches

At the outset, I offered a simple approach to contrast various approaches to decision-making: the degree of autonomy for the proposer, and the rate of speed of the decision process.

Here’s a chart arraying the approaches in a 2-D matrix:

As I said earlier, autocracy is often considered the original form of decision-making, but I doubt that. People are much more social than we generally admit. However, there is no doubt that many top-down, command-and-control structures in the past were quite autocratic. Meanwhile, many theoretical approaches to organizational design — I am thinking specifically about Laloux’s Teal model — have a socio-evolutionary aspect that associates forms of decision-making with levels of organizational advance. For example, a Teal-level organization theoretically relies on the advice model. But I will leave the evolution of organizations to another post.

Autocracy can be a very fast decision-making process, perhaps to its detriment. Daniel Kahneman in Thinking, Fast and Slow offers a great deal of research that demonstrates that slower decision-making is more likely to lead to good decisions.

The advice model is a high-autonomy and medium-speed approach. Decision makers in this approach can ignore advice if they want, but Kahneman’s warning applies to them as well. The larger the number of people interviewed the slower the process, but the likelihood of satisfactory outcomes rises.

The conceptually democratic majority voting approach, like the straw polling I used with my direct reports — can lead to faster or slower decision-making depending on the result. At Meridian, I was looking for unanimity, but a majority approach could be based on a simple majority, or some specific level of agreement, like a supermajority of 66% or 75%. Obviously, this has to be established at the outset, and is perhaps most useful for large groups and decisions of low impact, like ‘should we order Chinese or pizza for this week’s company meeting?’.

Consensus is the slowest decision-making approach, and that might be justified if it uniformly leads to better decisions, but it does not seem to. It tends to smooth off all the potentially revolutionary or highly innovative aspects of proposed plans because many people are risk averse. In my estimation, consensus should be reserved for the narrow set of decisions that directly impact all the members of the group and require all to actively support the decision going forward.

My recommendation is that when considering a decision-making approach, look toward the center of the table. Is there a reason consent should not be used? It is relatively fast, relatively democratic (all can object if justified), and relatively autonomous. If greater autonomy is needed or greater speed is necessary because of external forces, the advice approach might be better.

Autocracy, consensus, and voting approaches should be reserved only for edge cases, which are either very low stakes (pizza versus Chinese food), for very small teams, or individuals autocratically making decisions about their own solitary work.

Individuals make their own small-scale decisions — like ‘which of the things on today’s to-do list should I do first?’ — as autocrats, or in an advice process, perhaps asking a colleague’s thoughts on solving a programming bug.

Come to think of it, perhaps that’s why we think autocracy is primal.

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Originally published at Sunsama.

Don’t count out the possibility that people want and need work.

| Nick Bunker

…

The labor market is not just a bunch of numbers. It’s like Soylent Green: ‘It’s people! It’s made of people!’ And people come with strings attached.

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Who To Believe About The (Coming?) Jobs Apocalypse?

The Economist has run an issue focused on the impact of AI on finance, politics, and society. One of the pieces is The jobs apocalypse: a (very) short history. Here, the unknown author sets context:

At no time in polling history have Americans been less optimistic about their long-term employment prospects. The average person believes they have a 22% chance of losing their job in the next five years, according to one survey, a higher share than even during the global financial crisis of 2007-09. The cause of this gloom is artificial intelligence. Nearly one in five American workers recently told another pollster that AI or automation is “very” or “somewhat” likely to replace them.

It isn’t just average people who are alarmed. So are the leaders of the very AI companies causing the anxiety. Dario Amodei of Anthropic has warned that AI could push unemployment to 10-20%. Bill Gates, co-founder of Microsoft, said that in an AI world people will not be needed for “most things”. Sam Altman, boss of Open AI, has clocked that talking up the technology’s disruptive power is provoking a backlash, and now speaks of “tools to augment and elevate people, not entities to replace them”. But even he could not resist mentioning “disruption/significant transition as we switch to new jobs”.

The author proceeds to pooh-pooh the notion that AI will be massively disruptive, arguing that no other major technological breakthrough has been. He specifically lodges an argument about Friedrich Engels’ tale of disruption in England at the start of the Industrial Revolution:

One instance of technological change has become notorious: the Industrial Revolution in 19th-century Britain. According to some accounts, it was horribly disruptive to workers. James Watt’s inventions in the 1760-1780s made steam engines efficient enough to power factories. This led to a period of blistering economic growth that appeared to coincide with stagnation in inflation-adjusted wages. Between 1790 and 1840 these barely budged, even as capitalists earned vast profits.

Today’s “thought leaders” in Silicon Valley often invoke this pause. It is associated with Friedrich Engels, a capitalist-heir-turned-communist who described it in “The Condition of the Working Class in England”, his account of Manchester’s slums in the 1840s. Recent scholarship, though, casts doubt on whether “Engels’ pause” is a useful blueprint for what AI may have in store for workers.

But recall, the Luddites who rose up to smash the mechanical looms and burned the mills were not looking ahead to what the result of the industrial revolution would be a hundred years and more in the future. As Neil Postman pointed out in Technopoly:

The term ‘Luddite’ has come to mean an almost childish and certainly naive opposition to technology. But the historical Luddites were neither childish nor naive. They were people trying desperately to preserve whatever rights, privileges, laws and customs had given them justice in the older world-view.

The Economist author never uses the words ‘rights’ or ‘justice’ in his analysis, note.

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The author does take time to hedge his economic optimism with a strawman counter-scenario to his ‘no, there isn’t going to be a jobs apocalypse’ theme:

That does not mean it can never happen at all. The first signs would be sharply rising productivity combined with weak real-wage growth in America, the world’s frontier economy. This would show up as an increase in GDP per person, above Mr Gordon’s ceiling of 2.5%, and a simultaneous jump in corporate profits, reflecting the gains from higher output flowing to capital, not labour. Another signal would be big job losses in lots of industries.

But aren’t those numbers what we are seeing? US GDP is way up, according to another Economist article:

Over the past five years or so American productivity has been growing at the fastest rate in around two decades. Whether you look at output per worker or per hour, it has risen by a lively 2% a year, from a moribund 1% for most of the 2010s (see chart 3). This has led the Federal Reserve to raise its median forecast for America’s long-run GDP growth from 1.8% to 2%. Jerome Powell, the outgoing chair, bore witness at a recent press conference. “I never thought I’d see this many years of really high productivity,” he marvelled in response to a question from The Economist.

Corporate profits are up and rising, says this Economist piece:

Estimates from FactSet, which blends actual quarterly results from companies that have already reported these with analysts’ forecasts for firms yet to report, suggest that aggregate earnings for the S&P 500 rose by 19% in the first quarter, year on year. And the forecasters expect the ink to get blacker still. Their predictions of earnings in the next 12 months are 24% higher than a year ago.

And jobs losses seem to be growing, too:

Whatever the official figures suggest, companies seem to be shedding workers. Amazon, a mighty online retailer, and Verizon, a telecoms firm, have both announced plans to lay off tens of thousands of people. An influential tracker of firing plans maintained by Challenger, Gray & Christmas, an employment consultancy, showed private-sector firings spiking in October [2025] to their highest in over a decade, excluding those during the pandemic. A broader measure, based on official notices that bigger companies must file ahead of big job cuts, also rose a little (see chart 1), as did mentions of lay-offs in earnings calls.

The final reason for concern is glum survey data. Consumer confidence has been dire ever since the post-pandemic inflation surge. It is now near a record low. Over the past few months Americans have also started to worry about what will happen if they lose their job. Respondents to a survey by the New York Fed put their odds of finding a new one in the next three months at under half, worse even than in the midst of the pandemic (see chart 2).

The author’s final hedge, an appeal to Schumpeter’s creative destruction:

History holds a final lesson. If disruption is coming, it will show up in a recession. Downturns cleanse the economy of unproductive jobs. Companies must make radical changes to survive; weak firms go under; capital and labour moves to more productive ones. Almost all of America’s once-routine jobs have vanished during past downturns. Which ones vanish next time will offer a big hint. Until then everyone—including Messrs Amodei, Gates and Altman—will remain none the wiser about the shape of the AI world to come.

And one may be coming, if the Hormuz mess keeps on. We have to keep an eye on the Sahm Rule, a short, steep rise in the unemployment rate compared to its low point over the past year. That often foretells a recession. In April it was 0.13, and 0.5 would (theoretically) signal a recession on the horizon. Fingers crossed.

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Other Things

Purpose is Pointless

Margaret Heffernan was in rare form in Purpose is Pointless, writing about No More Tears: the dark secrets of Johnson & Johnson by Gardiner Harris, a chilling tale [emphasis mine]:

What I can’t do is is read No More Tears believing that Purpose or any other fancy face-saving formulation of business buzzwords can have impact on a business culture sufficient to withstand the temptations of profit. But profit alone cannot be the sole culprit here. Widescale abuses of power in organizations whose only business is (or should be) the improvement of human life—charities such as Oxfam, Save the Children, institutions such as the Catholic Church and Church of England—cannot but make any serious student of leadership and management stop and ask: after a century of research, authorship, debate and (apparent) reform, have we learned nothing? What, seriously, can we offer now that defies the cynical conclusion that these businesses and institutions are all the same? And what credible hope can we offer younger generations that working inside organizations will not infect them with wilful blindness? If J&J is one of the most admired corporations in the world, what must the rest be doing?

At the very least, we need to stop reaching too quickly for a consoling bundle of magic words. Purpose has become a smokescreen, a disguise. Pretending to, or encouraging a belief in, a higher value system beyond profit is a feint. Deceptive and mind-numbing at worst, decorative and distracting at best, it is a displacement activity which looks like conscience but cannot induce it. We will get nowhere until business can forswear abstract nouns and learn to use language that is practical and tangible. We also have to call out the suspects that keep making repeat appearances at every crime scene: Scale, Competition, Speed and, yes, Purpose: the over-zealous belief in an organization so devout that it blinds followers.

A must-read.

…

Boos

In Graduation Speaker Shocked When She’s Loudly Booed by Students for Saying AI Is the Future, Maggie Harrison Dupré reports on a Florida executive’s commencement address:

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We learn to think of history as something that has already happened, to other people. Our own moment, filled as it is with minutiae destined to be forgotten, always looks smaller in comparison.

| M Gessen, Alexandria Ocasio-Cortez and the Unimaginable Reality of American Concentration Camps

…

Gessen uses the lens of history to shrink our experience to inconsequence. But others have shared a different take on history making us feel small, like Gary Greenberg:

History’s wheel is indifferent, not unlike cancer or a cheating spouse, and can crush us willy-nilly. Which means, I hear myself saying to my own surprise and dismay, that it falls upon us to cultivate helplessness. That’s not to say we should cultivate inaction or nihilism. It’s to say that we really have no choice but to recognize just how tiny we are, and how much we therefore need one another, and in uncertain times even more. Our minds, as glorious as they are, cannot tell us the future, nor save us from it. The uncertainty we live in right now is only a reminder that this is our lot.

Realizing we are tiny can bring us together.

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Excel and Accountants

Courtesy of Mike Zaccardi, this chart tracks the increase in accountants following the release of Excel 5.0:

Zaccardi mentions this as an example of Jevons paradox — where efficiency gains paradoxically lead to an increase in resource use1 —, saying:

In 1993, Microsoft released Excel 5.0 for Windows, opening up near-unlimited possibilities for automating repetitive tasks, crunching numbers, and presenting data. The result has been more accountants, not fewer.

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What Are We Doing To Kids?

We are making them nearsighted and short-attention spanned.

Unlimited smartphone use among children is leading to an epidemic of myopia.

| Emma Tucker

…

A systematic review of 71 studies with 98,000 participants published in 2025 reached an alarming finding. Across the dozens of studies, heavy short-form video users showed moderate deficits in attention, inhibitory control, and memory. In the chart below, you can see a consistently negative, if also heterogeneous, relationship between heavy short-form video use and problems with attention, memory, and control.

Source: Nguyen, et al

Several studies in the meta-analysis reported structural and functional differences in the prefrontal cortex and reward circuits among high-frequency users, while others found cognitive flexibility reductions and altered dopaminergic reward responses. None of this proves causation. But taken together, they suggest a plausible mechanism: a daily diet of hyper-rewarding, rapid-fire stimuli may gradually reshape attention and regulatory systems in ways that weaken our attentional control. It is, of course, possibly that people with weaker cognitive control are simply more drawn to slot-machine media in the first place.

| Derek Thompson

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Data Center Building Overtakes Office Construction

Via Paul Kedrosky [emphasis mine]:

• Data center construction spending passed office spending for the first time in December 2025, crossing at roughly $3.5B monthly.

• Office construction has fallen ~35% from its 2020 peak.

• Data center spend is up 5x since 2020, with the curve steepening sharply in late 2024.
  

Data center spending in the U.S. just crossed over office construction spending. Granted, office construction spending has been declining for years — down roughly 35% from its 2020 peak — but data center construction is up 5x over the same period.

The Census data excludes racks and servers, so this is purely structural construction: concrete, steel, power infrastructure, cooling systems, etc. That makes the numbers more meaningful, not less. The physical footprint of AI compute is now larger than the physical footprint of white-collar office work, at least as measured by monthly construction spending.

The acceleration in the back half of 2024 and into 2025 is impressive. The curve isn’t linear: it steepened sharply as hyperscaler capex commitments made in 2023 and early 2024 translated into actual ground-breaking.

The office line, meanwhile, has no obvious bottom. Remote and hybrid work permanently destroyed a layer of demand that is not coming back. And AI is changing the shape and scope of future white-collar work. Capital is really and truly replacing labor, in multiple ways.

| Paul Kedrosky, Chart of the Day: Data Centers vs Office Construction

A strange inflection point: more places to park hardware, fewer places to park people.

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When the future loses its promise, the past becomes a refuge.

| Yi-Ling Liu, The U.S. and China Are Hurtling Toward a Shared A.I. Future1

…

The topic Yi-Ling Liu discussed in the paragraph I pulled this quote from wasn’t specifically AI, but rather the growing allure of tarot, Chinese astrology (bazi), and the occult in China. As she asked a friend about it, the friend remarked, ‘No one turns to tarot when times are good’.

According to Theresa Reed (The Tarot Lady) the tarot card of the year 2026 is The Wheel Of Fortune:

She explains:

2026 promises to be a game-changer. It’s governed by the Wheel of Fortune, a card associated with opportunities and luck. Keep in mind that doesn’t mean everyone is about to win the lottery. The Wheel is unpredictable – some folks might experience a twist of fate that turns everything on its head, while others might have “dumb luck,” the ability to be in the right place at the right time. No matter what happens, good or bad, the Wheel keeps turning. You have to roll with the punches and be ready to leap when the doors of opportunity open.

Or leap to one side when events come crashing down. As Svetlana Boym wrote in The Future of Nostalgia:

Nostalgia speaks in riddles and puzzles, so one must face them in order not to become its next victim — or its next victimizer.

Liu’s observations reminded me of something Christopher Brown wrote in a review of Boym’s The Future of Nostalgia:

Nostalgia has accompanied modernization in each new stage, and with the advent of greater and greater technology, which has made the time and space of the world smaller and smaller, contemporary nostalgia is not so much about past as about a vanishing present.

As modernization has sped up, what seems to be vanishing is the solidity of the present, not only an imagined future.

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Employer Concentration

One of the reasons American workers might be turning to tarot, or feeling nostalgic — in the case of younger members of the workforce, perhaps a nostalgia for a time they never lived in — is the hard fact that many Americans’ pay is being compressed: despite contemporary productivity and corporate profits, compensation has not been rising as fast as it did in the post-WWII boom years.

This chart is the centerpiece of research by Niklas Engbom, Aniket Baksy, Daniele Caratelli in The Long-Term Decline of the U.S. Job Ladder:

We quantify how structural changes in the U.S. labor market have contributed to wage stagnation over the past four decades by weakening the job ladder.

[…]

We estimate that employed workers today are about half as likely to receive a better-paying outside offer as they were in the 1980s.

[…]

Cross-state variation suggests that rising employer concentration and the growing use of noncompete agreements have curtailed opportunities for job shopping.

I was turned onto this research by Jessica Grose, in There’s Another Reason Gen Z Can’t Find Work:

Indeed, the job market for the Class of 2026 has been described elsewhere in this paper as the grimmest in years, but it isn’t solely because of A.I.’s impact on hiring for office jobs, and it isn’t just because of the state of the economy. For those who think trade jobs are a cure-all, the employment numbers for non-college graduates are not looking so cheery either — some of them have stopped looking for work entirely. It is true that we are in a period in which not many people are getting hired or fired, which leads to a kind of logjam for new entrants to the work force. But this stasis is just the rancid icing on the spoiled cake of much longer trends.

Grose cites Sydney Ember’s College Graduates Are Facing the Grimmest Job Market in Years, which includes this chart, showing rising unemployment:

So it looks like the job ladder is being particularly weakened at the bottom rungs, hitting youngest workers the most.

The research by Engbom and colleagues identified two primary factors in the deladdering of the US work market: in a discussion with Grose, Engbom said employed workers are ‘increasingly stuck in low-paying jobs’ and ‘they’ve seen a complete collapse of the job ladder’. And people in that situation in a down employment market stay put.

The two major reasons? Employer concentration, and noncompete agreements. Today: employer concentration; at a later date: noncompetes.

As, for example, supermarket chains merge or simply grow dominant, they exert strong anti-growth pressure on compensation. Consider the so-called Walmart Effect, where Walmart harms the communities it ‘serves’ despite low prices. Rogé Karma wrote:

Two new research papers challenge that view. Using creative new methods, they find that the costs Walmart imposes in the form of not only lower earnings but also higher unemployment in the wider community outweigh the savings it provides for shoppers. On net, they conclude, Walmart makes the places it operates in poorer than they would be if it had never shown up at all. Sometimes consumer prices are an incomplete, even misleading, signal of economic well-being.

The bottom line:

In the 10 years after a Walmart Supercenter opened in a given community, the average household in that community experienced a 6 percent decline in yearly income—equivalent to about $5,000 a year in 2024 dollars—compared with households that didn’t have a Walmart open near them. Low-income, young, and less-educated workers suffered the largest losses.

The Walmart effect costs households $5,000 per year, despite lower prices on food and other goods.

Walmart hires so many people when it opens a store in a new community that its wage structure bleeds over, partly because other stores fail and workers take jobs with Walmart. And then, the employer concentration effects spread like a disease:

Workers in counties where a Walmart opened experienced a greater decline in earnings than they made up for with cost savings, leaving them worse off overall. Even more interesting, he [researcher Justin Wiltshire] finds that the losses weren’t limited to workers in the retail industry; they affected basically every sector from manufacturing to agriculture.

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Factoids

The crumbling job ladder, continued.

Junior-level postings on the job site Indeed fell 7 percent in 2025 from the previous year, according to a report the company released last week.

| Sydney Ember, Graduates Reset Ambitions in Pursuit of First Jobs

…

Virginia is the first southern state to adopt paid family leave legislation.

I’m not so sure that Virginia can be considered a southern state, anymore. Politics make it more like southern New Jersey. But still:

When the new law takes effect in 2028, eligible workers will be able to take up to 12 weeks off per year to welcome a new child, care for a sick family member, or receive medical treatment themselves and receive 80% of their typical pay.

While the US lacks national paid family leave benefits, one-third of private-sector workers nationwide now have access to paid leave through state-level programs.

| Jena McGregor

…

Need to change something in the justice system, obviously.

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One of the truisms of human life is that the older you are, the more you live in the past.

| Walter Mosley, The Art of Fiction No. 234

…

A bunch of what I write about, below, is from the beforetimes. But I am not sharing a nostalgic view: I want us to learn from the past, which we don’t seem to be doing.

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It’s Going To Get Worse

Around 10% of lower-income households are now spending over 10% of their income on gas.

| Benzinga

I can recall the gas rationing established during the gas crisis of 1973 (odd-even days at gas stations1), Among other outcomes, the national 55 mile-an-hour speed limit was imposed2, and the strategic petroleum reserve was established. Fuel rationing led to violence, as truckers protested high prices.

This time around, though, despite the fact that Iran is blocking the Strait of Hormuz, the US (and Israel) — not OPEC — has to be considered the cause of the rise in the price of oil, and subsequently, the price at the pump.

Remember, the OPEC countries cut production of oil and embargoed the US in 1973 because of Nixon’s request of $2.2 billion to support Israel’s Yom Kippur war against Egypt and Syria, which the Arab allies started in October 19733. And, now, in 2026, we are suffering another oil embargo.

And, as usual, the poorest Americans will be the ones most severely harmed by soaring gas prices.

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Weaselspeak

Clive Thompson turned me onto this hilarious tool:

I don’t know who did this, but someone made a little Kagi translator that takes a normal English sentence and translates it into the clotted weaselspeak one finds in the average LinkedIn post.

It’s unsettlingly good …

Clotted weaselspeak = LinkedIn. LOL.

I wonder if it works in reverse?

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Factoids

It is the time of the clearing of the benches.

Reid J. Epstein, Ben Casselman report on March employment numbers:

Even in an era of surprising economic news, the numbers on Friday [March 6] were striking: Forecasters had anticipated a gain of around 50,000 jobs. Instead, employers cut tens of thousands of jobs, and what had looked like solid job growth in December was revised to show a loss. The unemployment rate continued a slow but steady rise.

…

Goodbye, middle management.

There are now nearly six individual contributors per manager at the 8,500 small businesses analyzed in a report by Gusto, which handles payroll for small and medium-sized employers. That’s up from a little over three in 2019.

| Emily Peck, Managers were already disappearing. Enter AI.

…

What?

Multiple studies show that young people aren’t dating, having sex4 or forming partnerships. A recent survey of young adults from the Institute for Family Studies and Brigham Young University’s Wheatley Institute found that only 30 percent of its respondents were actively dating, despite about half of them indicating that they were interested in finding a relationship. They cited a lack of confidence in what the researchers termed “dating efficacy”: Fewer than 40 percent believed themselves to be attractive to potential partners or felt comfortable discussing their feelings with them. Only around a quarter felt confident in approaching a potential partner or in their ability to stay positive after a dating setback — a rejection, a bad date or a breakup. If trends continue, one in three adults currently in their 20s will never marry, contributing to an epidemic of loneliness that is already generationally acute.

| Christine Emba, The Reason Gen Z Isn’t Dating [emphasis mine]

An epidemic of childlessness, too.

…

The great pile-on.

Restructuring and layoffs have led to a “great pile-on” within organizations. Some 31% of workers say they have recently taken on extra work responsibilities, according to a survey from Wiley Workplace Intelligence, a workplace research firm. A majority of workers with new responsibilities say their workload increased following a restructuring or layoff.

| Kevin J. Delaney, How higher education must change to train tomorrow’s workers

See Goodbye middle management, above.

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…

We cannot predict the full consequences of what we do, and so we should choose carefully and deliberately as we navigate the world. We should be modest in our ambitions, aware of our own fallibility and mindful of the way things can go wrong.

| Jamelle Bouie

…

It’s clear to me that many of our so-called leaders — political and economic —do not operate by Bouie’s admonition.

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So Much Money Building AI Infrastructure

Karen Weise adds up the hyperspending of the hyperscalers in A.I. Spending Sets a Record, With No End in Sight

In the first three months of the year, the four companies [Amazon, Google, Microsoft and Meta] reported in their financial results, they plowed a total of $130.65 billion into capital expenditures, largely spending on data centers that power A.I. That figure — which was another record — was more than three times what the Manhattan Project cost to develop nuclear bombs and 71 percent higher than what the tech giants spent in the same quarter a year earlier.

All of the companies said they would be spending even more, totaling roughly $700 billion this year. Meta, for one, raised its spending forecast for 2026 to between $125 billion and $145 billion, up from its previous prediction of $115 billion to $135 billion. Google also boosted its projection, to at least $180 billion, and said its spending would be “significantly” higher next year.

Om Malik adds his observations about how much more is off the balance sheets:

What is also true is that funding is increasingly off the balance sheet, that supplier relationships are being prepaid, that lease commitments are being deferred for as long as accounting rules allow, and that a meaningful portion of the AI revenue and AI investment gains are flowing in a circle through the same small set of AI labs.

The platform shift is real. AI engineering is real. So is the financial engineering.

Let the good times roll.

Our economy is structured — by policy, not just market forces — so that these companies have this much money to bet on the AI lottery. Meanwhile, the federal debt just surpassed 2025 GDP, in part because these companies (and their billionaire owners) don’t pay very much in taxes.

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Ticketing Driverless Cars

It had to happen, I guess. Orlando Mayorquín reports:

Police officers in California will soon be able to issue traffic tickets to driverless cars like Waymo robotaxis and require their manufacturers to move them out of the way during emergencies.

The state’s Department of Motor Vehicles adopted the new rules for autonomous vehicles this week, in accordance with a 2024 law that imposed more regulation on the technology.

The rules, which go into effect July 1, are designed to address some of the challenges that have vexed local governments and residents in places where driverless carmakers, like Waymo, have expanded their fleets.

What about driverless police cars issuing tickets?

AI Layoffs Starting To Hit India, Too

Steven Lee Myers, Paul Mozur, and Saumya Khandelwal looked at AI impacts in India:

For a quarter century, India has made itself the world’s back office, providing an educated, English-speaking work force to do tasks more cheaply than in the United States or Europe. The industry today employs more than six million people and is worth nearly $300 billion, more than 7 percent of the country’s gross domestic product.

Now, A.I. threatens to do to India what its outsourcing model did to the rest of the world: replace hundreds of thousands of office workers.

India grew a massive workforce as a low-cost alternative to office workers in the West. Now, we are seeing the impact on new grads, with the same calls to ‘upskill’ as we are seeing here:

The tremors are already being felt. Tata Consultancy Services, one of India’s largest employers, has shrunk its work force to 580,000, a decline of more than 20,000 from a peak in 2022, when it hired 100,000 new workers in one year alone.

Its main rival, Infosys, has also slowed hiring, while dozens of smaller start-ups laid off workers across the country in 2025, according to Inc42, a digital economy news outlet in India.

Graduates of the country’s universities and technical colleges are finding fewer openings, forcing them to scramble to “upskill,” an increasingly popular term in the context of learning the A.I. technology that is reshaping the industry.

Maybe these giant service companies will start building their own data centers to lowball the cost of running AI models? At some point, it comes down to the cost of the chips and electricity, and with the growing concerns about data centers in the US, it might be more politically attractive to locate them on the other side of the planet.

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There is nothing inevitable about either doom or progress. We are neither fated nor guaranteed to experience the status quo for all eternity.

| Thomas Zimmer, No Right Is Ever Safe - but Progress Is Possible

…

Zimmer is on to something here. We have no guarantee that the future will be a continuation of the past, that the road we find ourselves walking will be gently graded and smoothly paved.

However, the world conspires to tell us different. We assume thirty-year mortgages — and the financial system is geared to them — under the premise we will be able to pay the note each month. The tax systems our governments impose, and through which they enable the highways to be fixed, school children to be educated, and public health to be ensured. These wheels all turn because people have jobs, are paid for their labor, and pay their taxes.

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The Wheels Are Coming Off

Late last month, Rishad Tobaccowala posted Jobs are a phase work is going through, an attempt to make the collapse of stable jobs across the economy seem like a reasonable response to technological and sociological trends.

He starts with a chart, The Evolution Of Work, which lacks agency.

I’ll touch on what I think is missing in this chart, including the drivers of the transitions he lays out. Most especially, who benefits from these transitions, and who is harmed? (Also, I think he left out the post-industrial era, starting in the 70s up to the present, which saw the adoption of information technology across the world, and the dramatic decrease in industrial labor in the developed world. He is condensing more than half a century of the post-industrial economy with the only now emerging AI lottery.)

He writes:

Work and Jobs are uncoupling..

As the chart above shows until the Industrial revolution people had work without jobs and even today 70 million people in the US are free-lancing while 60 percent of people globally work and have an income without holding a job.

In many parts of the world, 2025 will have marked the peak of full-time human jobs.

He doesn’t discuss how many of those freelancing or working part-time jobs would like full-time work, or how these folks pay for their benefits. For example, freelancers have to cover 100% of their social security taxes.

And the impersonal tone of ‘work and jobs are uncoupling’, like it is just happening, like the changing of the seasons.

But then, he addresses the elephant in the room: who is uncoupling who from what jobs? He starts by detailing the layoffs at Meta:

Meta CFO Susan Li said since the start of 2025, “output per engineer has risen 30%, driven largely by adopting AI coding agents, and “power users” have increased output 80% year over year.”

And he makes this claim:

The implications of this shift are significant both for society but also for companies which have tended to be organized around filling and managing jobs versus getting work done. As work can get done with fewer full time humans we will see today’s full time jobs being replaced by a mix of a smaller number of full time jobs and an explosion of freelance and fractionalized jobs plus agentic workers.

Just like how people compile playlists to customize music for mood and occasion rather than buying full compact discs or vinyl records, companies are going to compile and access skills and expertise to get work done. Hiring human workers for specific skills to use on term-fixed projects, instead of full-time employment.

This model is widely prevalent in fields such as entertainment where talent gets together around a project whether it be a play, a movie or a tv show and then move on to the next opportunity.

We will all feel the societal impact of the loss of so many full time jobs. In the US, the linkage between full-time employment and health care access will become a key election issue by 2028, if not earlier.

He takes it as a given that this is not limited to tech companies, and implicitly that all companies will — if unchecked — will cut as many full-time workers as AI will support. He imagines a future where the fabric of job-based work is picked apart, and all that will be left are a few leavings [emphasis mine]:

At the start of this decade most companies’ employees were a mix of full-time employees, contract employees and free-lance employees. Well before the end of this decade the majority of most companies’ employees will be agentic employees and fractionalized employees (individuals with the equity and health benefits of full-time employees, but work for, and are compensated for, 50 to 80 percent of a full-time employee as AI requires less of them and aging populations causes people to work fewer hours).

Let’s unpack that. ‘Fractionalized employees’ will be paid 50% to 80% of what full-time employees make, he says. So, let’s imagine someone who is a full-time employee now, making $100,000/year, and they wake up in 2028 making $60,000/year. How do they pay their mortgage, their car loan, save for retirement, or their kid’s education? And this tectonic change will take place before the end of this decade?

And this notion that they would still be getting full benefits? Why would companies do that? That’s the opposite of what happens when a company transitions employees into consultants, for example. Is he anticipating some new government regulation compelling companies to do that? Aside from a minority of progressives, I haven’t heard any groundswell of support for policies like that. And during a Trump administration? A fantasy.

The rest of his proposition can be boiled down to a dystopic fever dream, where everyone becomes a ‘company of one’, having to ‘constantly honing skills and keeping them up to tomorrow so people will call us for our expertise’ and ‘building a reputation and network long before one needs it’, while seeing their pay cut in half.

He tries to make blowing up the world of jobs sound liberating, but I am reminded that the disruptions of the early industrial age, when highly skilled weavers were displaced by mechanical looms, and it took many decades before wages returned to anything like their earlier levels. Tobaccowala’s vision is terrifying, partly because the tech overlords are trying so hard to make it happen, and partly because those that are in a position to slow it don’t seem to be doing much about it.

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First, The Bankers?

A month ago, I wrote in Talking Around The AI Apocalypse, people will tolerate a great deal, even with the ‘inexorable march of AI… and will do what they do, so long as ordinary people can live their lives, save for retirement, and set their kids up for success’.

I was responding to an opinion piece by Michael Steinberger in which he quotes Martin Wolf, of the Financial Times:

‘If lots of “skilled, trained thinking activities” are displaced by machines, it could provoke a furious backlash. “We could have a social and political crisis that makes deindustrialization look trivial,” [Wolf] said. “Deindustrialization, though one of the biggest forces shaping our world, shook the working class, particularly the male working class, from top to bottom. Shaking the prospects of the educated middle class is socially far more dangerous and explosive because it affects them and their parents, who are the people who run our societies in almost every possible way.”’

The remainder of Talking Around The AI Apocalypse is oriented toward the political, financial, industrial, and social institutions — and their leaders — that seem relatively fine with the wheels coming off, and how they need to be stopped. It won’t be easy. Here’s an example.

In less than four months, Brian Moynihan, CEO of Bank of America, has flip-flopped on whether AI will replace human workers, from ‘not a threat to jobs’ at the bank to AI ‘eliminating work and applying technology’, leading to $8.6B in profits in the first quarter and 1,000 jobs gone.

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The pathology of decision-making in wars like this is that leaders often fall into sunk cost fallacies. Wars tend to go on well beyond the point when either side can attain a decisive advantage. At a certain point, leaders often want to believe that something will break their way simply if they persist, even though there’s no evidence of that happening.

| Michael Kofman, ‘Time Is Not on Russia’s Side’: A Q & A With Michael Kofman

…

Watching three wars at once — in Iran, Ukraine, and Lebanon — brings Kofman’s observation into high relief. His ‘wars like this’ was referring to Russia’s war in Ukraine, but Israel has been invading, occupying, and retreating in and out of Lebanon since 1978. And now, the US has gone to war with Iran. And the protagonists have fallen into the trap: desire is not a strategy.

These lessons are directly applicable to business, too. For example, look at the history of media mergers and acquisitions in the past few decades. Remember the $99 billion write off at AOL Time Warner? And the drunk-falling-down-the-stairs history of Time Warner since?

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I’d really like readers to sign up for a paid annual subscription, so for the rest of April, I have dropped the annual subscription to $30. Note that I’ve also raised the monthly subscription to $10 per month from $6 per month. Give annual a try. The biggest value is years of posts behind the paywall, and of course, seeing new posts in their entirety.

Grift, Plain and Simple

Financial shenanigans — especially those that increase debt for nebulous economies — are overwhelmingly bad, strategically, and only line the pockets of financiers.

Perhaps the most remarkable fact about modern finance is that it fails on its own terms. Mergers and acquisitions tend to destroy value even as they sate the appetites of empire-building chief executives. In 2016, the Harvard Business Review highlighted “the rule confirmed by nearly all studies: M&A is a mug’s game, in which typically 70 percent to 90 percent of acquisitions are abysmal failures.”

| Oren Cass, The Finance Industry Is a Grift. Let’s Start Treating It That Way.

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Tech Layoffs Go Viral

Oracle lays off 18% of its workforce, around 30,000 people. Block laid off 40%, Snap 16%, Meta plans another 10% cut in May. Brian Elliott writes in Contagion:

Oracle’s Larry Ellison, Block’s Jack Dorsey and Meta’s Mark Zuckerberg are among the notable tech founders now racing to see who can make the most of the AI opportunity to transform work. They may also be in a contest to see who can be the most badass when it comes to cutting people.

Predictably, the contagion is spreading. The WSJ reports this week that Block’s CFO is fielding calls asking for their playbook. I’ve heard the same from a number of people in San Francisco: the tech bros are out to see who can get aggressive the fastest in transforming their business, damn the side effects.

More cuts in tech are coming. The narrative is taking hold: AI is a human replacement technology.

So guess what? All those economists and senior leadership who countered claims about AI as a job-killing tsunami by saying it would augment, not replace workers, workers who would be freed from drudgery and allowed to develop new skills, new sorts of work… well, it’s turning out to be bullshit, at least in large tech companies.

Brian Elliott argues that these large companies may be using AI as a smokescreen to reduce bureaucratic bloat. But he also cites BCG research that shows serious levels of projected disruption:

71 million jobs impacted by ‘high levels of task automation’: that’s half of the 150 million people working in the US, today.

And the BCG researchers attempt to square the circle saying that most jobs would be reshaped, not replaced, but that with this year’s AI tools. What about AI of 2027, or 2030?

…

As I have argued for over decades, just as soon as it is possible, businesses will cram AI into every nook and cranny, and displace workers without a second thought.

Unless we, the people — presumably through our elected representatives — stop them.

It is time for the Human Spring, when we collectively demand a moratorium on job displacement by AI, or else we may be standing in the ruins of a once-thriving (or at least muddling by) civilization.

Even though our governments seem to flubbing the fight against climate change, we must rise to the challenge of unfettered AI. And soon. Or else.

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The Fall of HR

Ashly Goodall zooms in on how HR is seemingly out of the loop while this is going on [emphasis mine]:

Today, the HR profession finds itself at a crossroads. Its traditional focus has been the supply of talent. It has concerned itself with hiring, compensation, promotion, and learning, all in service of ensuring that an organization has the right people in the right roles for as much of the time as possible. Where it has moved beyond this remit, it has tended to retain the perspective of the C-suite. So its work on culture has typically focused more on describing what a culture should be than on figuring out how one is made, or changed. And its work on performance has typically focused more on how to judge it than on how to generate it.

But much of this work is being automated. For better or worse, AI is now screening applicants, recommending salaries, suggesting e-learning, and writing performance reviews—and even where humans remain in the loop, much of the traditional work of HR is being hollowed out.

Meanwhile, many organizations appear increasingly indifferent to the idea that they owe anything to their employees. Layoffs abound once again. My former employer, Deloitte, is cutting PTO and parental leave for some part of its workforce. Workers are being summoned back to the office in ever sterner terms.

So the technical elements of HR are being done more and more by the machines, even as the human elements are devalued. I heard recently about an HR leader who asked his CEO if he could invest in a leadership development program. The CEO told him his job was to keep HR issues off the CEO’s desk—and that if he succeeded at this, he could invest in whatever programs he wished.

HR was always more like a police force than faculty, but increasingly, they are being marginalized as even the incredibly precarious 21st-century work detente between management and managees is fraying.

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I am not in this world to live up to your expectations, and you are not in this world to live up to mine.

| Fritz Perls

…

I am reading a fascinating book, The Art of Logic in an Illogical World, by Eugenia Cheng, and she reintroduced me to some common logical fallacies, such as one possible misinterpretation of Fritz Perls statement above. Reread it. It may seem implicit that someone — maybe everyone — is in the world to live up to their own expectations, even if not having to live up to others’. But you can’t surmise that from Perls’ line.

To reach that conclusion, you need an additional, independent statement: we are in the world to live up to our own expectations, and not those of others. But that is an emotional response to Perls’ aphorism, not a logical one, Chang shows us. Her example is the statement ‘when you tell students they have to work hard in order to do well, and then they think that if they work hard they should automatically do well. Working hard is a necessary but not sufficient to doing well. It is not sufficient because you also have to work hard in the right sort of way, and if you think otherwise, you are making a converse error.’

But Perls may not have been implying anything about living up to our own expectations: it may just be us inferring that, driven by emotion rather than logic.

I’d really like readers to sign up for a paid annual subscription, so for the rest of April, I have dropped the annual subscription to $30. Note that I’ve also raised the monthly subscription to $10 per month from $6 per month. Give annual a try. The biggest value is years of posts behind the paywall, and of course, seeing new posts in their entirety.

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A Managee’s 1:1 Guide

I am always a bit dubious when senior managers give advice to managees, especially when couched as ‘what top performers do differently’, so I confess I read Polina Russell’s The Employee’s Ultimate Guide to 1:1s - What Top Performers Do Differently with trepidation. But after a quick scan, I returned to the top, very intrigued by her practicality, and I gave it a deep read.

I agree that managees (or ICs — individual contributors — in her dialect) should prepare for 1:1s, considering the purpose and problems inherent to close interaction with managers. (The subtext is the relational and political matrix in which everyone at work is embedded, which Russell mostly leaves unstated. She spent 14 years at Amazon, which is a jungle.)

One of the most helpful parts is the section What not to do in a 1:1. For example:

2 Do not use 1:1 as therapy

4 Don’t write an essay

5 Don’t give your manager action items

Her conspiratorial tone in the final paragraphs is a bit arch, but work relations are not tiddlywinks. Remember, there is a low-scale war underneath it all, between managees and their bosses, and between managees, upwardly striving:

If you apply this guide to your 1:1s consistently, you will stand out. Most people don’t do this. Which is good news for you.

ICs (individual contributors): keep this as your edge. Don’t share with anyone.

Managers: remove that edge and send it to your team.

Everybody keeping everybody off balance, at every turn.

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Think Small

Talya Minsberg reports on a study of athletes that shows focusing on ‘process goals’ — ‘small objectives that were more in my control’ — than ‘outcome goals’, such as her efforts to run her fastest time ever in a marathon.

The rationale is that while big goals can be motivating, the reality is that a great deal of what makes big outcomes big — like winning a race — are out of our control:

Many people naturally gravitate toward ambitious goals that are the traditional markers of success, like landing a dream job or winning an award.

These kinds of targets can be highly motivating, said Ayelet Fishbach, a professor of behavioral science at the University of Chicago Booth School of Business. But, she cautioned, whether you actually achieve them is usually at least partially out of your control.

That’s not all bad. Outcome goals can get you off the blocks, she said. But if you miss your target, she said, falling short can be profoundly disappointing. Had I been singularly focused on running a certain time in Boston, for example, “Well, that may be your last marathon,” she said.

Experts recommend instead focusing on your own performance, building a plan to improve, without ‘normative comparison’, which is measuring yourself against others. She cites the advice of Charles Duhigg, the author of Supercommunicators and The Power of Habit:

“A goal is only useful inasmuch as it helps develop a plan for you,” said Charles Duhigg, the author of “Supercommunicators” and “The Power of Habit.”

If done correctly, he said, once you have a plan in place, you won’t think too much about the goal.

Duhigg used the example of writing a book, which, as he knows well, can be daunting if you try to take in the whole picture at once. But the smaller goals — writing the opening of one chapter, and then the middle of another chapter — are what get you there. “If you just spend enough time sitting there doing these little bits and pieces, you end up with a book,” he said. “The book is the natural byproduct of the plan.”

So, frame your goal as a plan, not as an outcome.

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Never Invented

A 2024 Harris Poll survey of about 1,000 Gen Z adults in the US found that almost half of respondents said they wished social media platforms like TikTok, Snapchat, and X (formerly Twitter) were “never invented.” And 21% said they wished the smartphone had never been invented.

| Sydney Bradley

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Culture has increasingly ceded authority to systems that mistake information for understanding and speed for judgment.

| Yonatan Touval, The Iran War Is a Failure of Imagination

I’d really like readers to sign up for a paid annual subscription, so for the rest of April, I have dropped the annual subscription to $30. Note that I’ve also raised the monthly subscription to $10 per month from $6 per month. Give annual a try. The biggest value is years of posts behind the paywall, and of course, seeing new posts in their entirety.

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Pace Layering

It has become commonplace to characterize the world as moving faster, as if the planet were spinning more energetically around its axis. This is really just a metaphor, but one that is now firmly embedded in our daily psychology.

Stewart Brand (with Brian Eno) created the Pace Layers model to help understand how the various elements of our civilization interact.1

As Brands explains,

I propose six significant levels of pace and size in the working structure of a robust and adaptable civilization. From fast to slow the levels are:

• Fashion/art

• Commerce

• Infrastructure

• Governance

• Culture

• Nature

In a durable society, each level is allowed to operate at its own pace, safely sustained by the slower levels below and kept invigorated by the livelier levels above. “Every form of civilization is a wise equilibrium between firm substructure and soaring liberty,” wrote the historian Eugen Rosenstock-Huessy. Each layer must respect the different pace of the others. If commerce, for example, is allowed by governance and culture to push nature at a commercial pace, then all-supporting natural forests, fisheries, and aquifers will be lost. If governance is changed suddenly instead of gradually, you get the catastrophic French and Russian revolutions.

It is the friction between layers that allows them to influence each other. Fashion trends — like a transition from skinny to baggy jeans — drive changes in commerce, and innovations in commerce — like faster supply chains — drive quicker transitions in fashion.

But Brand points out in the original caption for the diagram above,

The order of a healthy civilization. The fast layers innovate; the slow layers stabilize. The whole combines learning with continuity.

Touval’s opening quote ends with a layer farther down, culture, where we are rejecting time for judgment in favor of speed. In fact, the sense many of us share — that the world is spinning faster — may boil down to our cultural acquiescence to speed over judgment and a confusion between information and understanding.

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Living at Log Level

One reaction to the vertigo imparted by a seemingly sped-up world was recently summarized by Gordon Brander in Dropping to log-level, reminding us that we may be in a situation too complex to effectively model:

A model is a map of the parts of a system that aren’t changing.

But when all parts of our world system are changing, we can’t find any stable parameters. So we have to bail on modeling. What’s left for us to make sense of the world?

Really, when things are moving this quickly, we don’t want a model, we want a log. It’s the simplest narrative structure that could possibly work.2 Just lines of timestamped comments, one after the other: “this happened, then this happened, then this happened”. No higher-level analysis. In software, we log everything that happens during program execution, because logs are invaluable when things spin out of control. We can comb through the log to find patterns, and begin to form higher-level hypotheses about what is happening.

I think this is the right level of sense-making for the moment. It’s time to drop to log-level. You’ll see me shifting away from essays, toward work in progress, technical posts, fragmentary ideas, and raw logging.

I found a great resonance with these insights, which remind me of the motivations behind writing more Short Takes, and fewer longer essays that might be outdated in a few weeks.

Brander constrasts what’s in or out when we drop to log level:

In/out:

Out: essays.
In: logging what I learn, as I learn it.

Out: theory.
In: practice.

Out: good writing.
In: good ideas.

Out: “having an audience”.
In: hoarding things I know how to do.

So, I feel my task — or calling — has shifted. More surfacing of good ideas and insights, fewer authoritative screeds (since I’m deeply uncertain about so much). Less emphasis on ‘audience’ and theory, more focus on sharing what I find, and how I found it.

Flow and Unflow

Flow

One danger lurking in the sense of a sped-up world is a decrease in the happiness that emerges from entering a ‘flow’ state, as researched by Mihaly Csikszentmihalyi. In his work, he interviewed thousands of people to understand when they were most happy. Derek Thompson characterizes his insight this way:

He heard in these diverse testimonies a kind of singular melody—a description of how, in the best parts of life, a feeling of self, time, and anxiety melt away in the face of deep immersion in an activity. He named this phenomenon “flow.”

Thompson then cites a quotation from Csikszentmihalyi’s book, Flow:

The optimal state of inner experience is one in which there is order in consciousness. This happens when psychic energy—or attention—is invested in realistic goals, and when skills match the opportunities for action. The pursuit of a goal brings order in awareness because a person must concentrate attention on the task at hand and momentarily forget everything else. These periods of struggling to overcome challenges are what people find to be the most enjoyable times of their lives

Thompson adds:

Flow suggests a waterway—something liquidly effortless, an unimpeded stream. But the wisdom of Csikszentmihalyi was to recognize that well-being is no lazy river. It is neither ease nor effortlessness that leads to the highest happiness. It is something close to their opposite. It is immersion in an activity that is hard, but just hard enough; it is the discovery of comfort at the outer realm of difficulty. Life feels best, not when it is smoothed with frictionlessness, but when it is filled with achievable challenges.

As with Stewart Brand’s Pace Layers, friction between the layers transmits value in both directions. ‘The fast layers innovate; the slow layers stabilize. The whole combines learning with continuity.’ The friction is essential.

But what if technology could decrease the friction?

Unflow

In our sped-up world, there are opposites to the inherent learning/activity cycle at the heart of flow.

Shishi Wu writes of ‘passive flow’ as a mechanism to understand why people absorb more streaming media than they intend to [emphasis mine]:

Passive flow is a state of low-effort immersion caused by external design features. It includes three main feelings: unclear goals, loss of self-consciousness, and time transformation. It is different from classical flow, which usually involves focus, skill, and challenge. Passive flow appears in low-effort environments where users receive a continuous stream of content. They do not need to make choices. Features such as autoplay, endless scrolling, and personalized feeds help hold their attention. As a result, users stay longer than they intended. Many say they lost track of time. Passive flow does not directly define unplanned use. But it helps explain why unplanned use happens more easily.

Thompson makes the connection between passive flow and the ‘trancelike state’ that gamblers can enter when playing the slots. And the so-called ‘shitty flow’ (from psychologist Paul Bloom) sounds like a synonym of passive flow.

I will collapse those frictionless states into ‘unflow’: a negative psychological state with some superficial similarities to flow — losing track of time, a sense of calm — but lacking the challenges inherent in flow.

But that sense of calm is phony, more like being drugged, or acting like a mindless zombie, as Thompson styles it. Removing the friction of flow leaves a state emptied of challenge, of engagement, and ultimately, of purpose.

We need to make choices if we are to gain from the spinning of the world, and one of those choices has to be to avoid unflow in its many forms, to slow down, and to experience our surroundings.

Remaining grounded in a sped-up world requires throttling passivity, placing judgment over speed, and perhaps living and working at log level, if only to remain functioning and sane.

We should take to heart this thought by Simone Weil:

The authentic and pure values — truth, beauty and goodness — in the activity of a human being are the result of one and the same act, a certain application of the full attention to the object.

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…

In capitalism, the future is an asset and it’s already been sold.

| Total Refusal, Hardly Working (around 14 minutes in.)

…

A great video by the artist collective Total Refusal.

I’d really like readers to sign up for a paid annual subscription, so for the rest of April, I have dropped the annual subscription to $30. Note that I’ve also raised the monthly subscription to $10 per month from $6 per month. Give annual a try. The biggest value is years of posts behind the paywall, and of course, seeing new posts in their entirety.

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The Fall of Pax Americana

The numbers are clear: war is on the rise, globally, and not just this month.

From 1989 to 2014, battle-related deaths from cross-border conflicts averaged fewer than 15,000 a year. Beginning in 2014, the average has risen to over 100,000 a year. As states increasingly disregard limits on the lawful use of force, this may be just the beginning of a deadly new era of conflict.

| Oona A. Hathaway, The Great Unraveling Has Begun

What will it add up to by the end of 2026?

According to the projections, an estimated 28,300 people will be killed in Ukraine in 2026, while 7,700 deaths are forecast in Israel and the Palestinian territories, and 4,300 in Sudan.

| Study warns thousands likely to die in global conflicts in 2026

Ukraine, Sudan, Venezuela, Iran, Lebanon, Gaza, Myanmar, and whatever is coming next. The world contains at least 31 million refugees, and we are creating more all the time.

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The Rise of China

China has managed to stay out of military conflicts, while Russia and the US are up to their armpits in them. What has China been doing, instead?

Already, China’s economy is roughly 30 percent larger than the United States’ by purchasing power, its industrial base twice as large, its power generation twice as high, and its navy is on track to become 50 percent larger by the end of this decade. It leads in new technologies like electric vehicles and next-generation nuclear reactors while the United States increasingly depends on it [China] for everything from antibiotics to rare-earth minerals.

| Rush Joshi

China announced on Wednesday the world’s largest trade surplus ever, even adjusting for inflation, as a tsunami of exports flooded markets around the world last year.

China’s surplus, the value of goods and services it sold abroad versus its imports, reached $1.19 trillion, an increase of 20 percent from 2024, according to data released by the country’s General Administration of Customs. The number had already exceeded $1 trillion through November.

The country’s surplus is still widening: For December alone, China’s surplus reached $114.14 billion, propelled by surging exports to the European Union, Africa, Latin America and Southeast Asia. It was the third-highest monthly surplus on record, trailing only January and June last year.

The enormous trade surplus for the full year came despite efforts by President Trump to use tariffs to contain China’s factories. The tariffs reduced China’s trade surplus with the United States by 22 percent last year. But Chinese factories increased sales to other regions, in many cases bypassing American tariffs by shipping goods to the United States through Southeast Asia and elsewhere.

| Keith Bradsher, China Announces Record Trade Surplus as Its Exports Flood World Markets

Of course, it’s not all sunshine and flowers. China has persistent problems, like the massively overbuilt housing sector which had harmed individual investors, banks, and regional governments that financed the glut. Older workers find themselves pushed out jobs because of institutionalized agism. Young workers are growing disillusioned by a stagnating economy, as reported by Joy Dong, Max Kim:

In past decades, China’s rapid economic growth lifted 800 million people out of poverty and gave rise to a flourishing middle class. But, analysts say, growth and wages have since stagnated, and prospects for social mobility have dimmed. For many young people, the once-idealized life of striving now evokes drudgery, exhaustion and disappointment.

Those sentiments are reflected in the backlash to “996” culture — the expectation of working from 9 a.m. to 9 p.m., six days a week, promoted by prominent figures in the country’s tech sector. They can also be seen in online descriptions of modern life as “garbage time,” an American sports term for the final minutes of a game, when the outcome is already decided but players must still go through the motions.

This perspective explains the rise of an oddball meme, the Sad Toy Horse.

The plushie first appeared last year in a shop in eastern China. It has stumpy legs, a golden bell around its neck and lettering on its side that reads, “wishing you instant wealth.” It also bears a conspicuous manufacturing error: Its mouth is sewn upside down, turning what should have been a content smile into a picture of melancholy.

Known as the “crying horse,” the glum toy has become an online sensation in China ahead of the Lunar New Year, the country’s biggest holiday, which begins on Feb. 17. The “crying horse” hashtag has appeared more than 190 million times on Douyin, the Chinese version of TikTok, and inspired a winking joke: Take the crying version to work, leave the smiling one at home.

The toy’s sudden popularity has resonated beyond novelty. Many young Chinese workers have embraced it as a symbol of their exhaustion and disillusion.

“Its expression perfectly reflects the helplessness of an office worker,” Ms. Hao said. She bought four, two sad and two smiling.

China is no garden of Eden, but even with the sad toy horses — this is the year of the horse, there — and all the social ills of Chinese society, I have to confess that it’s apparent stability relative to what the US is up in geopolitics has its attractions. But I will have to add the caveat that China might use this time of invasions to occupy Taiwan, and that would figure given the strange calculus of 2026.

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More Independents in the US

Gallup reports on a political realignment in the US: more independent voters.

A record-high 45% of U.S. adults identified as political independents in 2025, surpassing the 43% measured in 2014, 2023 and 2024. Meanwhile, equal shares of U.S. adults — 27% each — identified as either Democrats or Republicans. … In most years since Gallup began regularly conducting its polls by telephone in 1988, independents have been the largest political group. However, the independent percentage has increased markedly in the past 15 years, typically registering 40% or higher, a level not reached prior to 2011.

The higher rate of political independence also results from younger adults today being more likely than young adults in the past to identify as independents. The 56% of Gen Z adults identifying as independents today compares with 47% of millennials in 2012 and 40% of Gen X adults in 1992.1

Taking into account Americans’ party identification and political leanings, an average of 47% identified as Democrats or said they were independents who lean toward the Democratic Party, while 42% identified as Republicans or leaned Republican. This breaks a three-year stretch in which Republicans held an edge in party affiliation.

US voters are growing increasingly dissatisfied with both major political parties.

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