https://www.science.org/content/article/neurons-can-communicate-hidden-network-nanotubes-study-finds

the principles behind a successful exit from crisis remain relevant. While the specific policies will differ across societies, the overarching goal remains the same: to rebalance the distribution of wealth and power in a way that promotes long-term stability, not short-term elite enrichment.

Hundreds of societies have been in crises like ours. An expert explains how they got out.

No, we aren’t in “unprecedented times.” An analysis of 100 historical crises over two millennia has lessons for how society can avoid the end times.

^{Peter Turchin (Vox)}

How Trump’s Foreign Policy Is Ruining American Credibility

Keren Yarhi-Milo
October 2, 2025

For decades, U.S. foreign policy has depended on credibility: the belief that Washington would honor its commitments and that its past behavior signaled its future conduct. The United States, for instance, was able to develop a large network of allies because its partners trusted that, if attacked, Washington would defend them. It could strike free-trade deals with countries around the world and negotiate peace agreements because, generally speaking, it was seen as an honest broker. That is not to say the United States has never surprised, or that it never reneged on a promise. But for most of its modern history, it has been a trustworthy actor.

But unlike any U.S. president before him, Donald Trump has abandoned all efforts to make Washington reliable or consistent. His predecessors had also, at times, made decisions that undermined American credibility. But Trump’s lack of consistency is of an entirely different magnitude—and appears to be part of a deliberate strategy. He proposes deals before backing down. He promises to end wars before expanding them. He berates U.S. allies and embraces adversaries. With Trump, the only pattern is the lack of one.

The Price of Unpredictability: How Trump’s Foreign Policy Is Ruining American Credibility

Trump’s foreign policy is ruining American credibility.

^{Keren Yarhi-Milo (Foreign Affairs Magazine)}

Oggi, la giornata pareva aver incalzato un piede giusto (si può dire? boh!) — o, quantomeno, non marcio — sembrava che per una buona volta io potessi non soffrire — almeno, tolto il fattore meteo, che dalla sera alla sera stessa (letteralmente!) si è riconfigurato coi pinguini, e se adesso sono a casa senza un […]

octospacc.altervista.org/2025/…

caffettistica truffa delle macchine universitarie (la macchinetta del caffè rotta mi ha rovinato la giornata) - fritto misto di octospacc

^{minioctt (fritto misto di octospacc)}

The paper is here

The chart in Vox is particularly revealing, though I haven't found a gift link to it yet.

As you may know NOSTR (Notes and Other STuff via Relays) is another protocol for the fediverse like ActivityPub. In order to allow AP folks to communicate with NOSTR folks there are [at least] two "bridges" (mostr.pub & momostr.pink) created to allow certain level of server, client interaction between the two.

For some reason no lemmy communities nor users are ever found by either. It works just fine for mbin magazines and users. Do any of you have an idea why?

Automation undeniably has some useful applications. But the folks hyping modern “AI” have not only dramatically overstated its capabilities, many of them generally view these tools as a way to lazily cut corners or undermine labor. There’s also a weird innovation cult that has arisen around managers and LLM use, resulting in the mandatory use of tools that may not be helping anybody — just because.

The result is often a hot mess, as we’ve seen in journalism. The AI hype simply doesn’t match the reality, and a lot of the underlying financial numbers being tossed around aren’t based in reality; something that’s very likely going to result in a massive bubble deflation as the reality and the hype cycles collide (Gartner calls this the “trough of disillusionment,” and expects it to arrive next year).

One recent study out of MIT Media Lab found that 95% of organizations see no measurable return on their investment in AI (yet). One of many reasons for this, as noted in a different recent Stanford survey (hat tip: 404 Media), is because the mass influx of AI “workslop” requires colleagues to spend additional time trying to decipher genuine meaning and intent buried in a sharp spike in lazy, automated garbage.

The survey defines workslop as “AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.” Somewhat reflective of America’s obsession with artifice. And it found that as use of ChatGPT and other tools have risen in the workplace, it’s created a lot of garbage that requires time to decipher:

“When coworkers receive workslop, they are often required to take on the burden of decoding the content, inferring missed or false context. A cascade of effortful and complex decision-making processes may follow, including rework and uncomfortable exchanges with colleagues.”

Confusing or inaccurate emails that require time to decipher. Lazy or incorrect research that requires endless additional meetings to correct. Writing full of errors that requires supervisors to edit or correct themselves:

“A director in retail said: “I had to waste more time following up on the information and checking it with my own research. I then had to waste even more time setting up meetings with other supervisors to address the issue. Then I continued to waste my own time having to redo the work myself.”

In this way, a technology deemed a massive time saver winds up creating all manner of additional downstream productivity costs. This is made worse by the fact that a lot of these technologies are being rushed into mass adoption in business and academia before they’re fully cooked. And by the fact the real-world capabilities of the products are being wildly overstated by both companies and a lazy media.

This isn’t inherently the fault of the AI, it’s the fault of the reckless, greedy, and often incompetent people high in the extraction class dictating the technology’s implementation. And the people so desperate to be innovation-smacked, they’re simply not thinking things through. “AI” will get better; though any claim of HAL-9000 type sentience will remain mythology for the foreseeable future.

Obviously measuring the impact of this workplace workslop is an imprecise science, but the researchers at the Stanford Social Media Lab try:

“Each incidence of workslop carries real costs for companies. Employees reported spending an average of one hour and 56 minutes dealing with each instance of workslop. Based on participants’ estimates of time spent, as well as on their self-reported salary, we find that these workslop incidents carry an invisible tax of $186 per month. For an organization of 10,000 workers, given the estimated prevalence of workslop (41%), this yields over $9 million per year in lost productivity.”

The workplace isn’t the only place the rushed application of a broadly misrepresented and painfully under-cooked technology is making unproductive waves. When media outlets rushed to adopt AI for journalism and headlines (like at CNET), they, too, found that the human editorial costs to correct and fix all the problems, plagiarism, false claims, and errors really didn’t make the value equation worth their time. Apple found that LLMs couldn’t even do basic headlines with any accuracy.

Elsewhere in media you have folks building giant (badly) automated aggregation and bullshit machines, devoid of any ethical guardrails, in a bid to hoover up ad engagement. That’s not only repurposing the work of real journalists, it’s redirecting an already dwindling pool of ad revenue away from their work. And it’s undermining any sort of ethical quest for real, informed consensus in the authoritarian age.

This is all before you even get to the environmental and energy costs of AI slop.

Some of this are the ordinary growing pains of new technology. But a ton of it is the direct result of poor management, bad institutional leadership, irresponsible tech journalism, and intentional product misrepresentation. And next year is going to likely be a major reckoning and inflection point as markets (and people in the real world) finally begin to separate fact from fiction.

CNET had to correct most of its AI-written articles

CNET has issued corrections for over half of the AI-written articles the outlet recently attributed to its CNET Money team.

^{Igor Bonifacic (Engadget)}

404 Media

2025-09-23 15:41:11

AI ‘Workslop’ Is Killing Productivity and Making Workers Miserable

A joint study by Stanford University researchers and a workplace performance consulting firm published in the Harvard Business Review details the plight of workers who have to fix their colleagues’ AI-generated “workslop,” which they describe as work content that “masquerades as good work, but lacks the substance to meaningfully advance a given task.” The research, based on a survey of 1,150 workers, is the latest analysis to suggest that the injection of AI tools into the workplace has not resulted in some magic productivity boom and instead has just increased the amount of time that workers say they spend fixing low-quality AI-generated “work.”

The Harvard Business Review study came out the day after a Financial Times analysis of hundreds of earnings reports and shareholder meeting transcripts filed by S&P 500 companies that found huge firms are having trouble articulating the specific benefits of widespread AI adoption but have had no trouble explaining the risks and downsides the technology has posed to their businesses: “The biggest US-listed companies keep talking about artificial intelligence. But other than the ‘fear of missing out,’ few appear to be able to describe how the technology is changing their businesses for the better,” the Financial Times found. “Most of the anticipated benefits, such as increased productivity, were vaguely stated and harder to categorize than the risks.”

Other recent surveys and studies also paint a grim picture of AI in the workplace. The main story seems to be that there is widespread adoption of AI, but that it’s not proving to be that useful, has not resulted in widespread productivity gains, and often ends up creating messes that human beings have to clean up. Human workers see their colleagues who use AI as less competent, according to another study published in Harvard Business Review last month. A July MIT report found that “Despite $30–40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of organizations are getting zero return … Despite high-profile investment, industry-level transformation remains limited.” A June Gallup poll found that AI use among workers doubled over the last two years, and that 40 percent of those polled have used AI at work in some capacity. But the poll found that “many employees are using AI at work without guardrails or guidance,” and that “The benefits of using AI in the workplace are not always obvious. According to employees, the most common AI adoption challenge is ‘unclear use case or value proposition.’”

These studies, anecdotes we have heard from workers, and the rise of industries like “vibe coding cleanup specialists” all suggest that workers are using AI, but that they may not be leading to actual productivity gains for companies. The Harvard Business Review study proposes a possible reason for this phenomenon: Workslop.

The authors of that study, who come from Stanford University and the workplace productivity consulting firm BetterUp, suggest that a growing number of workers are using AI tools to make presentations, reports, write emails, and do other work tasks that they then file to their colleagues or bosses; this work often appears useful but is not: “Workslop uniquely uses machines to offload cognitive work to another human being. When coworkers receive workslop, they are often required to take on the burden of decoding the content, inferring missed or false context. A cascade of effortful and complex decision-making processes may follow, including rework and uncomfortable exchanges with colleagues,” they write.

The researchers say that surveyed workers told them that they are now spending their time trying to figure out if any specific piece of work was created using AI tools, to identify possible hallucinations in the work, and then to manage the employee who turned in workslop. Surveyed workers reported spending time actually fixing the work, but the researchers found that “the most alarming cost may have been interpersonal.”

“Low effort, unhelpful AI generated work is having a significant impact on collaboration at work,” they wrote. “Approximately half of the people we surveyed viewed colleagues who sent workslop as less creative, capable, and reliable than they did before receiving the output. Forty-two percent saw them as less trustworthy, and 37% saw that colleague as less intelligent.”

No single study on AI in the workplace is going to be definitive, but evidence is mounting that AI is affecting people’s work in the same way it’s affecting everything else: It is making it easier to output low-quality slop that other people then have to wade through. Meanwhile, Microsoft researchers who spoke to nurses, financial advisers, and teachers who use AI found that the technology makes people “atrophied and unprepared” cognitively.

Each study I referenced above has several anecdotes about individual workers who have found specific uses of AI that improve their own productivity and several companies have found uses of AI that have helped automate specific tasks, but most of the studies find that the industry- and economy-wide productivity gains that have been promised by AI companies are not happening. The MIT report calls this the “GenAI Divide,” where many companies are pushing expensive AI tools on their workers (and even more workers are using AI without explicit permission), but that few are seeing any actual return from it.

Microsoft Study Finds AI Makes Human Cognition “Atrophied and Unprepared”

Researchers find that the more people use AI at their job, the less critical thinking they use.

^{Emanuel Maiberg (404 Media)}

We are a family still trapped under ongoing bombardment in Northern Gaza.
We desperately need your help to evacuate to the south. Transportation costs have soared to over $2,000 — an amount we simply cannot afford.

Please, we are pleading for your support. Any contribution could help save our lives.
You are our lifeline. Please don’t leave us alone in this moment of despair
gofund.me/00439328

We are a family still trapped under ongoing bombardment in Northern Gaza.
We desperately need your help to evacuate to the south. Transportation costs have soared to over $2,000 — an amount we simply cannot afford.

Please, we are pleading for your support. Any contribution could help save our lives.
You are our lifeline. Please don’t leave us alone in this moment of despair
gofund.me/00439328

Shockingly, Perplexity says ‘the internet is better on Comet.’

Perplexity’s Comet browser is now available to everyone for free

Perplexity said its AI-powered web browser Comet and news service Comet Plus will be free to use globally.

^{Robert Hart (The Verge)}

US users stuck with AI ad targeting as EU users win more control over their feeds.

Meta won’t allow users to opt out of targeted ads based on AI chats

^{Ashley Belanger (Ars Technica)}