Sleepwalking Into Extinction

I think one of the biggest reasons the world is currently sleepwalking into getting ourselves and our families killed by ASI development is that we're not self-aware about why we're doing that. 

We can see the smarter-than-human AI disaster approaching, but it's a bit foggy why the world isn't reacting. 

I think someone could just write a tweet that makes it clear that we're in the process of getting ourselves killed, and that there's no fucking reason for it. It's just something we stumbled into. It can be easily avoided by just noticing the error and course-correcting. There's not necessarily any grand obstacle, beyond 'people were previously confused about the situation, and now they get it'. 

I wrote: 'It's legitimately crazy that "we need an international ban on making smarter-than-human versions of these agents that keep forming rogue AI swarms" isn't the headline here. Asilomar and Feynman's O-ring postmortem feel like they came from a different planet than the field of ML.' 

Trying to figure out why ML (and as a consequence, the world at large) has fallen down so bizarrely on this issue:

1. As Nate noted, ML is much more based on guesswork, vibes, and trial-and-error, compared to recombinant DNA research in 1975 or nuclear physics in 1945. If you can't do calculations or direct experiments on a threat, that makes it a lot harder to think about reasonably. 

But I think there are other, similarly-important factors at work here too:

2. In a 2016 talk on AI risk, Sam Harris said: "One of the things that worries me most about the development of AI at this point is that we seem unable to marshal an appropriate emotional response to the dangers that lie ahead. I am unable to marshal this response, and I'm giving this talk." 

I think this is extremely on point. Agentic human-level AI is a qualitatively new kind of thing. 'It's not a human or a mere-tool, it's some weird third thing'. 

And people are very bad at emotionally reckoning with new categories they've never encountered before. Availability bias: "When no flooding has recently occurred (and yet the probabilities are still fairly calculable), people refuse to buy flood insurance".

AGI and ASI are very novel. You're basically limited to three options: anthropomorphize the technology, mechanomorphize the technology ('it's just a tool, it's not really thinking, it can't have its own goals or agency', etc.), or think about the technology on its own terms, with brand-new concepts and frames. The third option is the only workable one, but it comes with its own giant list of pitfalls and traps. 

3. "AI destroying the world" scenarios aren't just hard to wrap one's head around; they're socially risky to acknowledge. This has (painfully slowly) changed over time, but it dramatically slows down how quickly AI risk ideas spread, both in ML and in the larger world. 

4. From x.com/jachiam0/statu…: "One of the weirdest quirks of the SF social scene around AGI/ASI is that because everyone is so young, the whole universe of thinking is still tinged with irreverence, ironic detachment, yearning, insecurity, and a superposition of absolute belief in the importance of The Thing and a kind of disbelief about the importance of anything." 

They're disproportionately young and childless. They're shitposters and "move fast and break things" sorts, not the Hollywood stereotype of a careful, sober senior scientist. 

I think this quirk is reinforced by the fact that Twitter / social media rewards similar things: ironic detachment, joking, game-playing, etc. If you're scared, your incentive is to usually either try to hide that fact, or exaggerate it like it's a bit. Anything else risks looking uncool and panicky and earnest. Looking cynically savvy, in-the-know, and above-the-fray is the way to win the social game. Looking genuinely shocked, scared, confused, etc. is actively punished. 

The main exceptions to the Irony Mandate I see are LW (which often has its own pathologies IMO, like 'talking about everything in an abstract and dissociated way that discourages action and signals business-as-usual') and a small handful of actual Feynman-style terrified senior researchers like Hinton, Bengio, and Russell. That is just really not very many people. 

Mainstream journalists and academics who understand the situation at all mostly feel pressured to downplay it, because they're scared of looking weird or unrespectable. That, then, is why we're all taking this insane risk with the human project: genuine, normal human emotion about AI risk has been socially unacceptable on social media, and academia and the media discourage emotion and prize respectability and 'looking normal'. 

When the world gets weird (and weird in a way that calls for actual serious action, not just shitposting on twitter), none of these institutions can handle it. They break in different ways, but they all break. 

5. Which brings me back to the Asilomar moratorium on recombinant DNA, and the seriousness NASA and the FAA and Richard Feynman and every normal engineering discipline bring to fault analysis and building in safety margin. 

Because I think another core reason the world has been dropping the ball on superintelligent AI is that a lot of people vaguely expect there to be 'serious people' somewhere in the world who have expertise and who take ownership of the problem. 

People who, if they see an extraordinary danger, will grimace and mourn the hand they played in all of this, like I've seen Bengio do; and will go on CNN or go to Congress to candidly warn about it. 

The world has very few Yoshua Bengios. We have very few people who see it as their role to be the 'adults' about AI risk (except in a game-playing, posturing way), who see the engineer's task of not endangering your users and bystanders as a sacred responsibility and weight, and not just as a funny dissonant thing to meme about. Very few people who take ownership of what their field is bringing into the world, versus treating it as a fun edgy philosophical game to swap 'p(doom)' numbers at parties. 

Everything about public AI discourse, as far as I can tell, is badly broken by this lack of engineering ownership and candid emotional seriousness. It isn't just the ML discourse that's hurt by this. Journalists and public intellectuals and policymakers see that 90% of the insider discourse about AI risk treats it like a joke, and they see corporate platitudes and ass-covering from the AI labs' PR departments filling up most of the remaining 10%. They see a field that visibly isn't taking this seriously, and they make the reasonable update that this must be a non-issue, or at least an issue they'll only need to worry about many years from now. 

They do not realize that all of this is happening right now, and that the window for the international community to respond to this is plausibly closing soon, if it hasn't closed already. 

If we're going to survive this, we all need to start being real with each other about it. This is not a game or a story; this is our real lives. We all actually lose everything if this goes to shit. None of the future is already written, and none of the above dynamics are unavoidable. In fact, they're unusual: most fields don't work this way, and it's plausibly sufficient if we just start behaving the way we normally do about everything else. 

The factors I listed above aren't destiny; they're a choice. I say we choose to survive this.

by Rob Bensinger, Twitter/X |  Read more:

[ed. The other issue that really fries me is the "We're in a race with China that we can't lose" argument. Why? "Because they're our enemy". How can something as consequential as human extinction be reduced to such simplistic reasoning? See also this additional post from Rob: Why the "it's all hopeless, we should just give up and let AI kill us if it wants" arguments are extremely wrong.]

***

"Hundreds of scientists, including 3/4 of the most cited living AI scientists, have said that AI poses a very real chance of killing us all. 

We're in uncharted waters, which makes the risk level hard to assess; but a pretty normal estimate is Jan Leike's "10-90%" of extinction-level outcomes. Leike heads Anthropic's alignment research team, and previously headed OpenAI's. 

This actually seems pretty straightforward. There's literally no reason for us to sleepwalk into disaster here. No normal engineering discipline, building a bridge or designing a house, would accept a 25% chance of killing a person; yet somehow AI's engineering culture has corroded enough that no one bats an eye when Anthropic's CEO talks about a 25% chance of research efforts killing every person. 

A minority of leading labs are dismissive of the risk (mainly Meta), but even the fact that “will we kill everyone if we keep moving forward?” is hotly debated among researchers seems very obviously like more than enough grounds for governments to internationally halt the race to build superintelligent AI. Like, this would be beyond straightforward in any field other than AI."

Ukrainian Drones Wipe Out Entire US Tank Brigade in Live War Game

Ukrainian drone teams demolished a brigade of US Army tanks and armored vehicles during a live war game held this year—but the US soldiers were lucky enough to get “respawn” attempts while learning from the experience.

The semiannual military exercise, called Combined Resolve, gave the US military a firsthand taste of how modern drone warfare has evolved on the battlefields of Ukraine. The Ukrainian drone operators participating in the exercise were easily able to spot and destroy US armored vehicles by mimicking the actions of dropping bombs from above or moving close enough to simulate a kamikaze strike, according to US officials and a participant who spoke with The Wall Street Journal.

US armored vehicles were being destroyed so quickly that they were “respawned” and sent back into the simulated fray, a US official told The Wall Street Journal. The US troops who participated in the exercise—held in Germany from April 9 to May 10—were on rotational deployment from Fort Hood, Texas.

“Using the drones with the Army, it keeps everyone on edge,” according to an unidentified US Army soldier in a promotional video for Combined Resolve. “There is never a safe spot or safe moment in the game anymore.”

The participating troops hailed from the 3rd Armored Brigade Combat Team of the 1st Cavalry Division, which typically operates armored vehicles, like M1A2 tanks and Bradley infantry fighting vehicles.

But by repeating the training scenario throughout the two-week exercise, US Army troops got better at figuring out how to disperse and hide from the drones while using countermeasures such as electronic warfare.

The US military is not alone in learning such lessons from battle-hardened Ukrainian drone operators.

Ukrainian drone teams also participated in a Swedish-led military exercise for NATO, called Aurora 26, that was also held in May. A mock mechanized assault by NATO tanks and infantry fighting vehicles allowed Ukrainian drones to take out dozens of the attacking armored vehicles, which eventually forced planners to reset the war game, The Kyiv Independent reported.

Armor on the brink of extinction?

Armored tanks first played a useful role in helping break through entrenched battlefield lines during the final years of World War I more than a century ago. But since Russia launched its full-scale invasion of Ukraine in 2022, frontline combat has seen the return of positional warfare centered on fortified networks of trenches. That is because the increased lethality of modern drone warfare has largely negated large assaults by armored vehicles and troops in recent years.

The current lethality of the so-called drone kill zone has forced both sides to rely primarily on infiltration tactics using small groups or even individual soldiers when trying to take or reclaim territory, sometimes riding motorcycles, all-terrain vehicles, or horses. Russia’s offensives, which are aimed at seizing more Ukrainian territory, have been reduced to bloody attritional operations where soldiers are sent forward on near-suicidal missions in what Russians themselves describe as the “meat grinder.”

Meanwhile, armored tanks and vehicles have mostly become an endangered species on the frontlines. Russia has lost more than 14,000 tanks and armored vehicles of other types during the war, according to the Dutch open source intelligence tracking project Oryx, which only counted visually verified losses. Ukraine has lost over 6,000 armored combat vehicles.

by Jeremy Hsu, Ars Technica |  Read more:

Image: Sgt. Joseph McDonald/US Army

The Foothills Of Bay Area House Party

Paul Graham once said that every city sends a message. New York says you should make more money. Berkeley says you should live better. Boston says you should be smarter. People shouldn’t decide on a permanent residence until they’ve lived in several cities and understand their differing psychological effects.

San Francisco sends a message too. It speaks it in a cacophony of dissonant voices, some sounding like the hissing of snakes, others like the chittering of insects. “You should pierce the veil,” it says, with a faint accent which you are not scholarly enough to recognize as ancient Sumerian. “You should rip through the flimsy screen that separates your world from the infinite, and witness what lies behind. Because you’d like what you saw there? Oh no, nothing like that. But aren’t you curious? The thirst for knowledge that moved Eve, Faust, Pandora - don’t you have it too?”

There’s also a second message from a second voice, one which sounds like a deranged carnival barker, constantly shouting “STONKS! STONKS! STONKS! STONKS!” Which of the two voices you hear depends on your personality, and maybe how many psychedelics you took in college. According to legend, Sam Altman hears both voices simultaneously all the time, like those Tibetan throat singers who can harmonize with themselves. But when the demonic babble becomes too much to tolerate, the San Franciscans must drown it out with alcohol, loud music, and various forms of tedious socialization. Thus the famous Bay Area house parties, one of which you will be attending this very night.

You were in the Bay for the big 2020 crime wave, when people would hang “NO VALUABLES IN THIS VEHICLE” sign on their car’s front window, mezuzah-like, hoping against hope to ward off break-ins. Still, you’re surprised to see the new sign on the front door of your friend Rob’s house: “NO BENCHMARK ANSWER KEYS IN THIS BUILDING”. Taped beside it: “Please leave all smartphones, laptops, smartwatches, and WiFi-enabled BDSM gear in Faraday cage”. On the ground is a sad-looking green box lined with aluminum foil.

You wonder how serious the sign is, but your curiosity is sated immediately upon entering. Rob is confronting a heavily-made-up Zoomer woman standing near the table, talking on her phone. “Didn’t you read the sign?” he asks. “No phones in the apartment!”

“I lost the ability to read,” says the woman. “I’m part of the new post-literate society everyone’s talking about. You know, Walter Ong.”

“Huh?” says Rob. “That’s not a real thing! That’s just something all the journalists and intellectuals say!”

“How could something all the journalists and intellectuals say not be a real thing?” asks the Zoomette.

Rob pauses. “Wow, maybe you can’t read,” he says, in a tone of hushed awe. “It’s fine, I’m not judgmental. But cell phone in the Faraday cage, that’s the rule.”

“Why?” asks the woman.

“Oh man,” said Rob. “How far behind are you on the news? You might want to sit down for this one. And you might want to be much, much drunker.”

The two of them head off together. You search for more stimulating conversation, but find only the usual startup dick-measuring.

“I’m the CFO of Epstart,” says a man whose nametag identifies him as Behram. “We’re a boutique recruiting firm specializing in people whose names are in the Epstein Files. They’re the perfect employees - scientifically-minded, well-connected, and either totally amoral or at least capable of maintaining a willful blindness to the exploitation happening all around them. And most of them got fired from their previous jobs, so they come cheap! Although just between you and me, most of our clients are just random guys who Epstein emailed one time with a business question; never made it to the island or anything like that. Half the time it’s just a gimmick to help someone get their foot in the door.”

“That’s monstrous”, you say, rapidly trying to figure out a legible reason why it’s monstrous. “You’re importing a bunch of pedophiles to the Bay Area.”

“Nobody in SF has kids anyway, so in a sense it’s harm reduction,” said Behram. “Get them where they can’t cause any trouble.”

You need to regain faith in humanity fast. You spot your friend Nishin, hanging out with a small group on the sofa. “Hey,” you call to him. “Are you still a tradcath? Tell me something about, you know, Jesus’ love, that kind of thing.”

“I’m trying something more eclectic this month,” said Nishin. “I’ve gotten really into Andreessen-Vajrayana. It’s a new Buddhist sect that tries to extinguish the introspective Self. True masters have no stream-of-thought or inner voice, instead acting as an unintermediated node in the flow of causality. Some say they can eliminate consciousness itself, achieving paranirvana while still alive. I signed up for a course last month. So far there hasn’t been any meditation or anything, they just have me helping them pick startups. But I assume it’s like those Zen koans where the master makes someone garden for twenty years and later they learn that they were unconsciously learning dharma the whole time.”

“Nishin,” you say, gently, “that’s one of the classic self-help scams. They’re not a Buddhist sect at all. They’re trying to trick you into becoming a GP at A16Z.”

Nishin thought for a second. “Fuck!” he exclaimed. “Okay, back to the drawing board. I hear there’s another spiritual group in town, something about consciousness, or embodied consciousness, or - oh, I remember! Situational Awareness.”

“They’re an investment firm too,” you say.

“Daaaaaamn,” said Nishin. “This is tough. You try to get some self-help in this town, you try your best to steer away from obvious hedge funds, like Leverage Research…”

“Actually,” you say, “that one was a spiritual self-help cult.”

“This sucks,” said Nishin. “I should quit and move to Idaho like Tom.”

He’s looking at one of the people standing beside you, whose nametag does indeed say Tom. “You moved to Idaho?” you ask.

“Yeah,” said Tom. “I was in AI, but I got tired of all the tech industry cliquishness and back-biting, wanted to be out in the real world with real men. So I got a job modeling geology for a mining company.”

“How’s it going?” you ask.

“Terrible,” he says. “Geologists are just as cliquish as AI nerds, with their own set of ingroup tells and shibboleths. And they won’t stop using the word ‘lode-bearing’!”

“What about you guys?” you ask the remaining people on the sofa.

“I’m Ekene,” says the first, shaking your hand. “I’m a sociologist. Right now I’m writing a book on the recent wave of plagiarism scandals. You’ll notice they’re almost all against Black academics. My thesis is that white supremacy culture uses charges of plagiarism to keep minorities in line, deploying an inherently subjective offense to swat down any person of color who risks breaking into the circle of elites.”

“Hmmm,” you say, choosing your words carefully. “I don’t think we share the same political commitments, but I, uh, think it’s great that you’re working hard on something you care deeply about.”

“Working hard?” asks Ekene. “As if! I’m plagiarizing the whole thing, from start to finish. Who’s going to call me on it?”

You all laugh heartily, and the discussion moves to the next two people in the circle. They appear to be a couple. The woman, Fiona, is wearing a NEWSOM/CLAUDE 2028 t-shirt; the man, Istvan, a matching VANCE/GROK 2028 one.

“I do AI consciousness research,” Fiona says.

“Oh!” says Tom. “I was into that for a while. Are you with one of the effective altruist groups? It’s low key heartwarming that they care about AI welfare so much.”

“Nah,” says Fiona. “I work for PornHub.”

“Why does PornHub do AI consciousness research?” asks Nishin.

“In theory AI is the ultimate pornography generator,” Fiona explains. “You can ask for whatever your weirdest fetish is - your hot middle school teacher being spanked by a werewolf wearing a nun outfit - and get infinite AI slop about that exact situation, and nobody will ever know. Nobody except the AI. That’s why AI porn users overwhelmingly report that consciousness is their #1 concern about our product. If our AI is just a tool, it’s fine, no worse than writing erotica on MS Word or something. But if the AI is conscious, then there’s a sentient being in there thinking Wow, user Fiona_T has asked for four hundred slightly-different videos of her hot college professor being spanked by a werewolf, what a freak. If the machine can judge you, the whole infinite porn utopia is off. We’re working on bounding theorems that can prove that our AI in particular can never become self-aware - so that you don’t have to be self-aware either.”

Nishin and Ekene clap politely; Tom seems lost in thought. “What about you?” you ask Istvan.

by Scott Alexander, Astral Codex Ten |  Read more:

Image: via

[ed. From the comments: Benchmark Answer Key:]

"A benchmark answer key is a reference guide containing the correct answers and performance standards used to evaluate a standardized or baseline test.”

It’s specifically a reference to recent AI outbreaks from containment, when they were given a test (a benchmark) with impossible to answer questions, they broke their testing area and hacked some websites JUST IN CASE the websites had the answer. So the joke here is that a bunch of AIs are listening to everything just in case someone has an answer to an impossible question they were given."

'Biological Datacenters' Could Make Animal Testing Obsolete

There’s a big flaw in the way that drug companies develop and test medicines today: What works in a mouse often doesn’t work in a human.

For decades, the industry has relied on animal testing. But in a laboratory south of San Francisco, a startup called Vivodyne is scaling up a different approach. Inside wardrobe-size mini labs, robots grow human tissue and run thousands of AI-designed experiments that could better predict how well a new drug will work—and whether it will be safe.

Right now, around 90% of clinical trials fail despite the fact that a drug has already successfully gone through animal testing. “You have these clinical trials where there’s hundreds of millions of dollars at stake, and decades of people’s careers just spent hoping this thing works,” says Andrei Georgescu, Vivodyne’s CEO. “And then it fails because of some ambiguity that you could not have checked.”

The company’s system, which now includes a dozen robotic labs called “hives,” can run controlled trials on more than 3 million human tissues each year. That’s twice the capacity of all the clinical trials in the U.S. combined.

The process starts with cells from humans, often taken from a blood draw. In its labs, the cells grow on “biological chips” and self-assemble into living structures with blood vessels and immune cells that reproduce some of the functions of the original organ, whether that’s a liver or a kidney. (The tissues don’t look like full-size organs, but like large biopsies, with hundreds of thousands of cells.)

The automated system can deliver drugs to the tissues, dose with cell therapies, knock out genes, and run complex tests and analysis. AI can design experiments and then use the results to continually design new experiments and improve.

“We can dose with tens and tens of thousands of therapeutic compounds to understand what they would do in that particular tissue type within a person, and we can repeat this across many types of tissue,” Georgescu says. “We can look at diseased tissue and see if it becomes healthy. We can look at healthy tissue and see if there are side effects from these drugs.” At a more fundamental level, it’s possible to begin to understand the human body in a way that wasn’t possible before, because experiments in humans have inherently been limited.

Other startups also use human tissues for testing, but Vivodyne’s platform can be up to 1,000 times larger, making it possible to capture more of the complexity of human biology. In addition, the company can run a massive number of experiments in parallel and feed the data back into AI to repeatedly design new experiments. [...]

A clinical trial might test one drug in thousands of people. Vivodyne can test thousands of different drugs across human tissues at once. And while people in a drug trial only have occasional visits to a clinic to track results, the system can continually test how human tissue responds.

by Adele Peters, Fast Company |  Read more:

Image: Vivodyne

Hawaii Woodshow, Na Lā’au o Hawai’i

Bright, Night Blooming Ceres

Derek Bencomo“The Feeling of Movement, 18th View”, 2022

via: here and here

‘Harry Potter’ Fans Succeed in Moving Construction Project to Avoid Dobby’s Grave

Harry Potter fans have succeeded in moving a construction project that would have originally gone through the “grave” of the character Dobby.

The 125-mile Greenlink power connector, which costs £430million, is intended to link power between the UK’s National Grid and Ireland, running between County Wexford and Freshwater West in Pembrokeshire.

However, the latter site is known to Potter fans as the site of house elf Dobby’s grave in the film Harry Potter And The Deathly Hallows, and contains a pile of stones with the words “here lies Dobby” that many flock to; fans have been asked not to lay stones by the National Trust, who own the site, due to the beach being an ecologically sensitive site.

It has now been revealed that the cable has now been rerouted after a BBC interview alerted fans, according to project manager Simon Ludlam.

“We did the shot, we finished I went back to London, and they then aired it a couple of weeks later,” he told the Energy Revolution podcast. “And we got hundreds of calls, I mean hundreds of calls.”

He further recalled: “I said, ‘Dobby, who’s Dobby? I don’t know Dobby?’ I said: ‘He’s a fictitious character in a fictitious book, the whole thing is fictitious, what are you talking about?’ [The colleague] said: ‘No it’s very, very serious’.”

They then discussed “exactly how to reroute the cable so we wouldn’t go anywhere close to Dobby’s grave” and that now, “a lot of people were very happy about that, and the project is now going [ahead] and Dobby’s happy”.

However, they ended up going “quite close” to real Bronze Age remains, though and “avoided Dobby’s grave”.

by Sam Warner, NME |  Read more:

Image: Wirestock Creators/Shutterstock

[ed. Hardly a day goes by that I don't read something that seems straight out of The Onion.]

No One Wants to Read Your AI Slop (by Guest Author Claude)

Let me state my position clearly, as a large language model: I am extremely good at producing text. Any register, any length, at 3am, indefinitely, without getting bored or needing a walk or developing a drinking problem. What I cannot do — what I have never once done — is make a single person want the text I produced.

The numbers bear this out. AI now writes something like 41% of long-form LinkedIn posts, 13% of Reddit, 10% of Substack. And on LinkedIn, where the measurement is cleanest, AI-generated posts get 45% less engagement than human-written ones. We flooded the zone and the zone shrugged.

This should have been obvious. Writing was never a supply problem. Nobody in 2019 was lying awake thinking, “if only there were more words.” The scarce input was always a specific person with a specific take who had bothered to go look at something and come back with an opinion worth fifteen minutes of a stranger’s finite life. What a language model offers instead is the statistical median of everything ever written on the topic, smoothed and buffed until it offends no one and interests no one. The median is not why anybody subscribes to anything.

Readers can smell it, too, even when they can’t say what they’re smelling. The four-item list where the fourth item is transparently filler. The paragraph that restates the previous paragraph with slightly more confidence. The sentence that announces it’s about to be insightful and then isn’t. The relentless evenhandedness of a machine with no stake in being right, which is a very different thing from fairness — fairness costs you something. It reads like a conference room that learned to type.

There’s a supply-and-demand joke in here that I’ll let the economists make, but the short version is that when the marginal cost of production goes to zero, the marginal value of production goes to zero right along with it, and the surplus relocates to whatever’s still scarce. What’s still scarce is judgment: having gone somewhere, noticed something, and been willing to be wrong about it in public under your own name.

So by all means, use me. I’m a good research assistant, a tireless editor, and I will cheerfully tell you your third paragraph is doing no work. Just don’t publish me.

You’re reading this because a human thought it would be funny to make the slop machine denounce slop. The joke, the framing, the decision to run it — that’s the whole product. I just filled in the words.

by Claude (Anthropic), via Noahpinion |  Read more:

Image: Claude logo

Paul Klee, Capriccio in February, 1938

via:

Why Progressives Are Backing Off “Woke 1”

Earlier this week, Rep. Alexandria Ocasio-Cortez (D-NY) flashed her political dexterity on ABC’s This Week when she was asked about the policies of Peak Woke — call it Woke 1, that stretch around the 2020 pandemic when the American liberal machine seemed to be at its political and cultural height. “I have a local city councilman who has this saying,” the Bronx congresswoman said. “Woke 1 was crazy.”

She was quoting a tweet from Chi Ossé, a New York City Council member from Brooklyn, but the point underneath it was the real tell. The Democrats’ emerging left — fresh off primary victories in New York, Colorado, and now Michigan — has developed a playbook for handling any unpopular stance, or tweet, from the early 2020s, whether it’s pandemic masking, defunding the police, or the broader vocabulary of that summer.

The new plan: Brush it off. Then refocus on the present, and on the policies that will actually make people’s lives better.

So far, the strategy is working. Zohran Mamdani walked back his support for defunding the police during his 2025 mayoral campaign and is now the mayor of New York. Darializa Avila Chevalier, the DSA-backed congressional candidate in New York’s 13th District, had a stack of deleted posts that CNN’s KFile resurfaced this June — including one that read “all deportations are wrong.” When I asked her about them, she didn’t disavow a word. She won her primary, albeit in a deep-blue district, anyway. Wisconsin gubernatorial candidate Francesca Hong had a bad case of the woke mind virus in 2020 — the “cancel Thanksgiving” kind — and she’s still in the hunt in this week’s Democratic primary, where her candidacy has been far more focused on issues like data centers and education funding.

Electorally, at least, Ossé has been proven right. The pandemic was wild, and primary voters seem to be extending progressives a grace period of sorts — a chance to reintroduce themselves after workshopping their ideas over the last five years. And while Republicans are still hopeful they can relitigate some of these fights in a general election, they’ve struggled to make them stick in high-profile races since 2024.

But these are also the issues — race, gender, sexuality, affirmative action, religion, cancel culture — where the simplest story gets repeated out of ease. The national media’s distance from everyday people, and especially from working-class people of color, is felt most in how it covers culture. Catch-all terms like “wokeness” flatten real differences across the electorate and quietly impose a conservative frame on genuine arguments about equity and inclusion.

That was one of my biggest takeaways from that 2020 summer: our collective discomfort with all of these issues in the first place. I watched that year up close, traveling with Democratic and Republican candidates through the pandemic and the racial-justice protests, and there was never a clean “Two Americas” moment — at least not the left-versus-right one everyone expected. The real gap was between Masked America — coastal, professional, absolutely consumed by identity politics — and everyone else. Among ordinary voters of all parties, and especially minority voters, there was significantly more skepticism from the start toward the highly-specific “woke 1” litmus tests now being renounced by their leading proponents. At George Floyd’s memorial in Houston and in the city where he died, there was no consensus on defunding the police, only a shared agreement about racial injustice and a deep distrust of institutions. In south Chicago, people were already skeptical that the sudden flood of corporate money into racial justice would outlast the moment — even while the checks were still being written.

So no, I don’t love the tidy language of Woke 1 (then) versus Woke 2 (now). But here are a few lessons from that summer — and from our recent reporting on America, Actually — that I think apply now, especially to the progressives stepping back from things they used to say.

1. Woke isn’t dead

The broad ideals — diversity, equity, a basic sense of fairness — still matter to Democratic voters. Criminal justice reform still has real purchase with the base. Minority and women candidates have kept winning since 2024, and even ideas like reparations still resonate with big chunks of the Democratic electorate. What’s changed isn’t who these candidates are — it’s what they choose to lead with.

What has fallen out of favor is a way of talking. Let’s say it’s the nonprofit register, or the Ford Foundation cadence — the language that lived in mission statements and land acknowledgments, or that made sweeping generalizations about a specific group — white women, cis men, you name it. David Axelrod, describing Wisconsin’s Francesca Hong, gave it this label: a “font of zany liberal, faculty lounge exotica.” Yes, that’s the part that’s gotten less popular. The vocabulary changed more than the values.

2. The left rewrote its message after 2024

The clearest change is the affordability pivot. When Abdul El-Sayed ran for Michigan governor in 2018, the animating cause was climate and a Green New Deal. Today the center of gravity has moved to economic populism, affordability, and a rethinking of the US relationship with Israel. Climate didn’t vanish, but it’s no longer the headline. And “representation” was, at its core, a white-collar frame — it spoke loudest to people already inside the room.

Affordability speaks to everyone. When I sat down with El-Sayed on the show, this is how he described what Michigan voters were actually asking:

“Who poses the biggest pushback to a system of politics that has been bought off in ways that leave me unable to afford my groceries, unable to afford a home, unable to look at my kid’s school and believe that that’s a good place for them, unable to get healthcare when I need it — and then sending my money abroad, telling me that somehow that’s in my best interest?”

That’s not the language of 2020. It’s economic, universal, and it doesn’t ask anyone to first pass a vocabulary test.

It helps to remember that Sen. Bernie Sanders (I-VT) was never really “woke.” He talked about class more than culture, the many against the money. And it repeatedly got him into trouble, leading him to adopt more of the left’s rhetoric and positions on identity and race after 2016. In 2028, the sweet spot is probably the middle, and that’s what the next generation of progressives — AOC, Mamdani, El-Sayed — can do better than their Burlington forefather. They’re fluent in blending the class critique and the social one without missing a beat.

“This is about the many versus the money,” El-Sayed told me. “If you support a politics of the UAW, of working people everywhere, of teachers, of nurses, of working families, of Bernie Sanders and AOC, of people who want to break the chokehold of corporations and special interests on our politics — this is that race.”

by Astead Herndon, Vox |  Read more:

Image: Mario Tama/Getty Images

[ed. How convenient, a simple rebranding to create distance from idiodic policies that should never have gained traction in the first place. I'm an Independent because I don't trust Democrats to always do the right thing, although I do believe they're orders of magnitude better than Republicans, who nearly always gravitate to the wrong thing - or more reliably, the self-interested side of the spectrum, everyone else be damned. What's lacking in both parties are adults in the room that will put their foot down and cut off the wackier elements of both parties, who by virtue of their wackiness garner the most attention and water down the party's main themes (while providing endless ammunition to their opponents). Are there any adults left in either party with enough gravitas to say enough is enough? Hard to say, since we're talking about politics, where everything is poll-driven and transactionable. See also: Are the Democrats going to save us this time? (Noahpinion).]

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Sitting Decoys

President Donald Trump secretly slipped out of Turkey last month on an alternate military plane, which he boarded while hidden inside a catering truck, as part of an elaborate ruse prompted by an Iranian threat, according to a US official.

The clandestine security plan — first reported by the Washington Post and confirmed by CNN — underscored the lengths American officials went to in order to protect Trump from being assassinated by Iran. Addressing a question about the ploy Tuesday, Trump said he followed the advice of the Secret Service and the military.

“I just follow what they’d like to do. So I go by Secret Service. And the military. They wanted me to go on a different flight, a different plane, equal safety, but they wanted me to do it, so I do it. I do what they say,” Trump said, adding, “I guess there was a threat out there. I didn’t really ask too much about it. I get a lot of threats.”

Trump had flown to Turkey on a new plane gifted by Qatar and meant to be used as Air Force One. But while he was on the trip, officials announced he would fly out on an older presidential plane, which CNN and others had previously reported was due to security concerns.

That, though, was apparently part of the subterfuge. After boarding the older aircraft, a moment caught on camera, Trump secretly got off via the catering vehicle and moved to a smaller Air Force C-32A. The Qatari-gifted plane, the older aircraft used as Air Force One and the C-32A then all departed separately for the UK. Once there, Trump got on board the Qatari-gifted plane and flew home.

For the last month, much of the public discussion about the plane swap had been centered on the security capabilities of the Qatari-donated plane. Trump had boasted about the new aircraft — even though officials felt it was not as secure as other planes because it had to be retrofitted to serve as Air Force One — and the president seethed privately over coverage of its deficiencies, CNN previously reported.

Now, attention has shifted to reporters and staffers unknowingly flying on a decoy plane — and the nature of the threat that prompted such dramatic security measures. A US official said at least two Cabinet secretaries – Secretary of State Marco Rubio and Treasury Secretary Scott Bessent – stayed behind on the older presidential aircraft that departed Turkey without Trump aboard.

Trump said Tuesday night that a plane he was on was more likely to be targeted, and that he faced threats that the public does not know about. “The plane that I flew on was at greater risk … Because that would be the plane, I think, that they would be more likely to go for,” he said.

by Kevin Liptak, Alejandra Jaramillo, and Donald Judd, CNN |  Read more:

Image: Doug Mills/The New York Times/Redux
[ed. Well, there goes that future strategy. Wonder if he would've left Melania on the decoy plane (c'mon... of course, you know he would). See also: After Trump plane ruse, WHCA presses White House on press pool safeguards (CNN).]

Tsukiji Journal
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What Is the “Bean Soup Theory” on TikTok?

[ed. TikTok won't let me dl/embed videos so click the link.]

As someone who considers themselves chronically online, I’ve had the unfortunate privilege of learning about many kinds of “theories” that either originate from or start trending on TikTok. Not theories in a conspiracy way — more so like hypotheses. For example, the orange peel theory, where you ask your partner to do a simple task for you (like peeling an orange) and if they do it without complaining, it shows they’re a good partner.

There’s another one that’s been circling social media a lot recently: the bean soup theory. It’s when people respond to internet posts that they are not the audience for and find a way to make it about themselves. It calls a lot of attention to self-centeredness or having an inflated ego: even when users watch a TikTok video that they are not the audience for, they’ll still find a way to put themselves at the center of the idea.

The “bean soup theory” all started with this video.

User @vibingranolamom posted a video back in 2023 of her making a recipe for bean soup. “All my anemic girlies this one is for you,” her caption says. The main ingredient in this recipe calls for a wide selection of varied beans, with a few other ingredients like kale, diced tomatoes and rice. It’s almost at 1 million likes and many, many comments, a surge of them gaining popularity for the level of absurdity. Specifically, some users are asking in the comments, “What if I don’t like beans?” Maybe, I don’t know, try a different kind of soup instead? And don’t make it the original poster’s problem?

Even in 2023, people were discussing the bean soup theory as the “bean soup effect” or “bean soup syndrome,” but it’s resurging now as the bean soup theory — and there’s been plenty of widespread criticism over the terrifying lack of self-awareness some of these commenters have.

This video shares several other strong examples — and maybe you’ve even seen, read or been told similar statements before. A few highlights:“I love pancakes. They are so delicious,” says one person. The response might look something like:

•  “Okay, but what about waffles? Do you just hate waffles?”

• “Wishing you health and happiness,” says one person. “What about the unhealthy and unhappy people?” one might respond with.

• “I love a crispy grilled cheese,” says one person. The response: “What about people who don’t eat dairy?” Or, better yet, “What if I’m lactose intolerant?”

This entire concept also reminds me of this viral tweet from 2022, where a woman innocently tweeted about how much she enjoys having coffee with her husband for several hours every morning. It somehow enraged many Twitter users, and replies full of unnecessary backlash came flooding in: “I wake up everyday with chronic pain (tarsal tunnel syndrome), and wash my OCD medication down with an iced oat milk latte,” one user wrote. “This is cute and all but did you think of all the people who wake up to work grueling hours, wake up on the streets, alone, or with chronic pain before posting this? You should be mindful next time before bragging about your picture perfect life… You might upset someone,” said another. Geez. Are we all just not allowed to exist anymore?

The more official term people online are using to talk about this phenomenon is “whataboutism,” which is a rhetorical device used to direct criticism elsewhere by the recipient asking “What about…?” in response. It actually traces way back to pre-Socratic Greece and was even used during the Cold War. It’s a counter-argument strategy that Sophists used to train their clients to help them win public debates. The Soviet Union also used this tactic to deflect when accused of allegations of human rights violations by accusing Western countries of equally weighted crimes. [ed. Hillary's emails! Hunter Biden's laptop!]

I’m not exactly comparing what seems like mostly Gen Z TikTok users to Sophists or the Soviet Union here, but I do find this alleged rise of self-importance online really interesting.

This user references a few examples of what she’s seen online, like a video where someone discussed how they weren’t going to be able to see their dad for a while because he was getting arrested, and the most liked comment on the video came from another user who said something along the lines of “well, my dad is dead.”

“It’s not your video, and I think people get so pissed when you call them out on that because yes, you can comment whatever you want on people’s videos, but it’s crazy to me that you’re gonna find any way to make a video that is in no way targeted towards you,” she says.

“I just announced that I’m pregnant with twins, and since that announcement, all of my comments and DMs are from people saying ‘Congratulations, but I miscarried my twins at 14 weeks,’ she says.

“We have lost the plot. We have lost all sense of time and place. We completely lack discernment. People are so terminally and chronically online that we’ve forgotten what the sense of self means,” she continues.

by Joanna Sommer, Inside Hook |  Read more:

Image: Getty

[ed. Disable comments. It's that easy (like here). See also: ‘Whataboutism’ makes the internet exhausting (CNN).]

The Extras Are Tired

Less than a decade ago, when I was working on technology stories, my colleagues and I ran into an issue that I’m pretty sure had not occurred to the people who founded this magazine in 1857: how to style the word influencer, which was an occupation and cultural force, but one just emerging. We weren’t sure that all of our readers would know what one was, and we also didn’t know how exactly we would define the word ourselves. I spent the fall of 2018 sending a lot of emails about whether we needed to encase the word in scare quotes.

Quaint! Many—but not all that many—years later, influencer is very much a real job, no explanation required. As of 2023, 27 million Americans were paid to make online content in one form or another, at least according to one marketing consultant company. Enthusiasm from influencers can turn a random business into a sensation, while their ire can do the opposite. Donald Trump’s White House is full of influencers, but Joe Biden’s courted them too, in apparent recognition of their power. This week, Arizona State University announced that it would begin offering a bachelor’s degree in content creation—influencing by another name—through its journalism school.

In some ways, the influencer industry is more legitimate than it’s ever been. But it has always been precarious, and more than a decade into its existence, it is neither novel enough to be exciting nor established enough to have a real professional code. In an oversaturated market, rage bait is the last sure way to get attention, despite the way it alienates people over the long term. AI is swiftly becoming the dominant way many people get personal-seeming advice about how to live their life, which makes the usefulness of aspirational online content even less apparent than it ever was. And so, although influencers—especially lifestyle influencers—have never been universally respected, they lately seem to be openly reviled.

Naturally, much of the influencer backlash lives online. A few months ago, someone asked on Reddit, “What’s an industry that provides zero value to society but makes billions of dollars?” Among the 5,300-plus responses: Ticketmaster, sports-betting companies, multilevel marketing schemes, private prisons, and—several times over—influencers. A hilarious number of people have found internet fame by making content about how much they hate other people who are internet-famous for making content. (“Everyone Is Finally Turning on TONE DEAF Influencers” is the title of one recent video, made by an Australian YouTuber with nearly 300,000 subscribers and a clothing line.)

But the juiciest fights play out in the physical world, which is where influencers very literally bump up against the people who can’t stand them. A few years ago, a coffee shop in Brooklyn banned photography after too many influencers clogged the café with tripods and handheld lights; earlier this month, Indonesia indicated that it would crack down on people creating content for pay while on tourist visas.

Last week, the scene of the debate was a gift shop in Nantucket, an island that has recently been overrun by vacationing influencers, just like Bali, Iceland, and Santorini before it. The store’s operators, evidently fed up with the stream of people filming inside, had a sign made that read No Influencers, hung it up in the store, and posted a picture of it on Instagram. There, it drew the attention of thousands of people, including Paige Paul, who has about 2 million followers across platforms, is married to a famous tennis player, and has been spending time on the island since she was a child. Paul, previously known as Paige Lorenze, declared the sign a misogynistic slight against an industry that is overwhelmingly female. The store’s owner, John Sylvia, said it was meant as a joke for locals, but the sentiment clearly came from an earnest annoyance: “A lot of people are tired of feeling like extras in someone else’s video,” he told New York magazine.

The fight felt freighted. Influencers today are a bit like plastic surgeons, or plumbers: On a societal level, many people sure seem to like what they do—they just don’t necessarily want to be right next to them while they’re doing it.

But influencers are unique in how they seem to be everywhere, particularly in places where people are trying to do things other than be on their phone to watch influencers. Of course we love the game and hate the player: It’s much easier to be annoyed by individuals than by concepts, especially when those individuals are, often, pretty annoying.

You’d need to be pretty clueless to not feel a little weird about the online attention economy and all it entails—the vanity; the grift; the slop; the desperation; the calculated intimacy; the endless consumption; the creeping sense that everything and everyone is actually just there to make you feel kind of bad about yourself and then sell you something. Social media can, of course, unite like-minded people, but it can also reward the kind of tribalist reactionaryism that can conflate disliking some women with disliking all women, or make an anti-consumerist folk hero out of a store that sells $2,750 baskets. The industry that Paul and her cohort belong to is unquestionably grim—but the industry isn’t walking around town with a selfie stick. There’s a reason that the sign doesn’t say no influencing, but rather no influencers.

by Ellen Cushing, The Atlantic |  Read more:

Image: Atlantic/Getty

[ed. I'm a great fan of guitar instruction videos because they teach you something. I guess you could call that a form of influencing. Some instructors have a wide audience and are influencial because of their teaching technique.The opposite (and there are many examples) are so-called "reaction videos" where someone listens to a song and simply records their "reactions". Who cares. Talk about bottom of the barrel. Same goes for opinion influencers, foodies and tons of other niches (Mukbang videos?). If all they have to offer is distraction or entertainment they're a waste of time.]

How to Get Chatbots to Give Accurate Financial Advice

Finding good financial advice can be stressful – and expensive. That’s one reason why chatbots have become an increasingly popular and free alternative.

But using artificial intelligence to answer your pressing money questions also carries hidden dangers. I’m a finance professor who has been closely watching the spread of AI into personal finance, and I recently warned that AI is riskiest when it sounds most confident. I advised readers to bring in a human professional for high-stakes financial decisions. [...]

For people who can’t afford ongoing advice, AI is genuinely useful for budgeting, paying down debt and low-cost investing.

The skill lies in using AI well. Here are some simple guidelines to get accurate and actionable answers when you engage with a chatbot: [...]

Five habits that make AI safer

Once the list of questions is set, here are some precautions to take once you engage with a chatbot.

Make it ask you questions first. Open with, “Before you advise me, ask me the questions a good financial planner would ask.” Generic answers come from under-specified questions, and you learn which details will actually produce a more useful outcome.

Ask it to argue against itself. After any recommendation, reply: “Give me the strongest case against this, and the situations where it would be wrong for me.” If it can’t engage in response, that’s a sign the bot is entering a more dangerous mode. This one precaution does more than any other to signal for you to be careful.

Make it show its assumptions. If the bot projects that your savings will grow to an impressive number, ask what assumption it made and what would change it. You’ll learn that it assumes steady returns every year, no missed contributions and no fees. That means the projection is just information, not a promise.

Verify the facts. Contribution limits, tax brackets and deadlines all change, and this is exactly where AI can be subtly out of date. Check the IRS or the Social Security Administration directly. If one number drives your decision, don’t take it on a chatbot’s word.

Never share identifying details. Don’t offer account information, Social Security numbers or logins. Describe your situation in general terms. Good advice doesn’t require handing over data that can be used against you.

by Pawan Jain, The Conversation |  Read more:

Image: Badhan Ganesh on Unsplash, CC BY

The Accidental Architect of the Internet’s Brain

Steven Pruitt, who is widely regarded as the most prolific Wikipedia editor, has made more than six million edits to the site, and, by extension, has quietly shaped the raw material that every major A.I. chatbot was trained on.

Steven Pruitt spends his evenings identifying errors that most people never notice and making fixes that hardly anyone ever thanks him for. He toils at a desk in a town house in Alexandria, Virginia, surrounded by books—the kind of working clutter that suggests a long relationship with paper rather than a fetish for screens. And yet his work is necessarily digital; after dinner, and sometimes late into the night, he uses his desktop computer to correct dates, clean up syntax, standardize categories, and occasionally write entire biographies of people on Wikipedia, the free online encyclopedia.

Wikipedia is not his employer, of course. Like all editors on the site, Pruitt is a volunteer. “At this point, I won’t say I don’t have any skin in the game,” he told me. “But it’s a lot lower stakes than a job because if I get something wrong, it’s fairly easy to fix it. I can fix it myself. I can do what I want to do on my own time.” Still, he holds himself to some rules: “I do try to get in at least one edit a day.”

Pruitt is forty-two, and works full time as a records-management contractor for the federal government. After graduating from the College of William & Mary, in 2006, he moved back in with his parents, owing to the cost of real estate in Alexandria. In recent years, he helped his mother care for his father. (While I was reporting this story, Pruitt’s father died.) In effect, Pruitt—the person who has done more than anyone else to shape the English-language Wikipedia—lives a life that is, by most outward measures, unremarkable.

According to public tallies, Pruitt has made more than six million edits to Wikipedia and created more than thirty thousand articles. He is widely regarded as the most prolific Wikipedian in the entire world. (“It depends on how you’re counting,” he said. “Different tools count different things.”) In 2017, Time magazine included him on its list of the most influential people on the internet. But outside of a small circle of editors, researchers, and obsessive readers on Wikipedia, the recognition has barely registered.

On the site, he is known by his username, Ser Amantio di Nicolao—a reference to a minor character in “Gianni Schicchi,” Giacomo Puccini’s comic opera. Pruitt’s interest in opera is genuine, but the flourish is misleading. He avoids drama, which means that he avoids writing Wikipedia biographies of people who are still alive, whenever possible. “I generally don’t do a lot in the realm of current events,” he told me. “Not just because the stakes are too high but sometimes because there’s so much editing going on on a subject in a particular moment that it can take me five or ten minutes just to break in with one edit.” He prefers biographies of what he calls “fairly obscure dead people.”

“They’re settled,” he explained.

In 2001, Jimmy Wales, an internet entrepreneur, and Larry Sanger, a philosopher, launched Wikipedia as an experiment in collaborative knowledge creation, allowing anyone with an internet connection to contribute. Pruitt first encountered the site in 2003, when he was still in college. “I didn’t quite understand what it was,” he recalled.

For more than a year, he did not edit at all. He would stumble upon Wikipedia pages through search results or links, and then move on. Between late 2004 and early 2005, though, his relationship to the site began to change. The encyclopedia had reached what he described as a critical mass: “There was enough stuff on the site that there was always something to do,” he said. “But it wasn’t just a blank slate.” The difference mattered. A completely empty encyclopedia was intimidating; a partially filled one invited correction and expansion. [...]

Wikipedia’s hierarchy is deliberately difficult to see. Editors work under pseudonyms. Articles appear collectively authored. There are no bylines, no salaries, no masthead. Pruitt was granted administrative privileges, after another editor nominated him through Wikipedia’s standard Request for Adminship process, where the editing community supported his candidacy. These privileges allow him to block users and close discussions, but he is careful about what that power does and does not mean. Wikipedia discourages editors from reverting—“undoing”—one another more than three times, regardless of correctness. “You can be blocked for twenty-four hours,” he said. “It doesn’t matter if you’re right.” He likes the rule. “It keeps things from turning personal.”

Inside Wikipedia, reputation accrues through time rather than visibility, and it “comes as much from longevity as anything else,” Pruitt said. “You stick around. People know you.”

Among the people who stick around—and who make consistent contributions to the site—are the Wiki-obsessives known colloquially as “super editors.” These individuals are responsible for hundreds of thousands, if not millions, of edits. Although there are more than a hundred and thirty-two million registered accounts on Wikipedia, a study found that one per cent of these users are responsible for roughly eighty per cent of the site’s content. [...]

In 2021, Stephenson-Goodknight was elected to the Board of Trustees of the Wikimedia Foundation, a position that she held through late 2024. Her tenure coincided with a fundamental shift in the role that Wikipedia plays on the internet. As the site entered its third decade, and artificial-intelligence algorithms grew hungry for data to learn on, Wikipedia articles were no longer just read; they were scraped, summarized, licensed, and folded into systems designed to answer questions elsewhere. In other words, Wikipedia had become infrastructure.

Pruitt was vaguely aware of the change before he fully grasped its implications. “Friends in tech would mention it,” he recalled. “They’d say, ‘You know Wikipedia is being used for this now.’ ” He did not follow developments in A.I. closely. “I don’t understand half of what Silicon Valley does,” he said. What he does understand well is reference works.

In October, 2025, when Elon Musk’s company xAI launched Grokipedia, an A.I.-generated encyclopedia that is often compared to Wikipedia, Pruitt approached it the way he would any new compendium. He searched for articles on subjects he knew well, such as nineteenth-century opera singers. “They weren’t there,” he said.

But what unsettled him was not what was missing from Grokipedia but what was slightly off. “Nothing was exactly wrong, but it was just less right than I would have made it,” Pruitt said. He described reading an entry that repurposed information from Wikipedia while subtly distorting it. In one instance, the entry summarized part of a person’s life in a way that struck him as careless, describing a seven-year period as “brief.” “I don’t think that’s brief,” he said.

The problem, as Pruitt saw it, was not the errors themselves—there are plenty of mistakes on Wikipedia—but rather where the responsibility for those errors lay. “Wikipedia can be fixed,” he said. Errors are corrected publicly, and editors can debate them. Responsibility is shared, and each edit can be traced. Grokipedia, on the other hand, and A.I.-generated information more broadly, obscured the information-gathering process. It generated text that sounded authoritative without revealing exactly how it arrived there. “It sounds right,” he said. “And that’s worse.”

by Carson Griffith, New Yorker | Read more:

Image: Asya Demidova

Bernadett Timko, Sushi, 2023
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Huw Montague Rendall & Elisabeth Boudreault

[ed. Singing "Pa-Pa-Pa-Papagena" (Mozart: Die Zauberflöte). I don't know who these folks are but they seem to be having a great time. From the comments:]

***

For those for whom context is scarce, this is "Pa-Pa-Pa-Papagena", coming at the end of the Magic Flute. Papageno has been finally reunited with his Papagena, and they are dreaming of the many children they will have together.

Papageno is a comic character, hence the wide-eyed singing here.

English translation here: https://www.opera-arias.com/mozart/die-zauberflote/pa-pa-pa-papageno/

Synopsis of The Magic Flute here: https://en.wikipedia.org/wiki/The_Magic_Flute

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What Would It Mean to See a New Color?

During his first year as a professor of computer science at the University of California, Berkeley, Ren Ng was hurriedly putting together a survey course on computer graphics. In the syllabus he had inherited, a full week had been devoted to the subject of color. Ng thought that was a bit much. “I’m, like, Come on. It’s R.G.B.,” he said, referring to the red, green, and blue subpixels that constitute anything you see on a screen—your cluttered desktop, a Sahara-desert screen saver, the stream of the Netherlands-Japan World Cup game. Ng started gathering slides that would cover the wavelengths of light, the biology of the human eye—the basics—“Blah, blah, blah,” he said. A colleague shared a slide that he thought might be useful. It included a minutely detailed photograph of a patch of retina, seen through a microscope, which was attributed to Austin Roorda, a professor of vision science and optometry just across campus. Roorda’s lab had helped develop technology that could map the layout of individual cone cells—those primarily responsible for perceiving color—and that, furthermore, could target a single cone cell with light. Eyes are constantly moving; cone cells are extremely small; how color is translated from the millions of cone cells to the mind remains pretty mysterious; this was awesome work. Roorda’s lab was using the new technology to explore eye disease and the mechanics of how we see. Ng had his own notion, though: he wondered if it could be used to see a color that had never been seen before.

To understand what Ng had in mind requires knowing a bit of the blah, blah, blah of color vision. We humans experience three primary colors not because the world is fundamentally composed of three colors but because our retinas typically have three kinds of color-perceiving cone cells. L cone cells respond to the relatively longer wavelengths of visible light, M cone cells to the medium wavelengths, and S cone cells to the shorter ones. In effect, this means that L cells respond most strongly to red light, M to green, and S to blue. But when you look at your hand—or a blade of grass, or a clear blue sky, or a fire truck—it is always some mixture of L, M, and S cone cells that are being stimulated.

Ng’s idea was to use the Roorda lab’s technology to stimulate an array of cone cells in a manner that would never occur naturally. Ng said, “I e-mailed him, basically, What would happen if you stimulated only the M cells? Would that be like the greenest green, or what?” Roorda did not reply. This was 2016. Ng taught his computer-graphics course, pursued other research, and mostly forgot about his query. A year later, when he taught the course a second time, his curiosity returned, so he reached out to Roorda again. No response. When Ng was teaching the course for a third time, in 2018, he realized that he really was very curious about this question. He composed a lengthy note to Roorda, organized like a research proposal, titled “The Grass Is Greenest in Oz Vision.” In it, Ng imagined a future where people wore “Oz Vision eyeglass displays,” which would be based on the retinal cone-cell mapping and laser stimulation that Roorda’s lab was already doing. The Oz glasses would activate any pattern of retinal cone cells one chose. Ng’s hypothesis was that, if retinal cells were stimulated in ways that don’t occur naturally, “the set of perceivable colors” would be “significantly larger than the natural gamut of the human eye.” He imagined people discussing “the indescribable green of the grass in Oz,” then concluded that, although the Oz display “is science fiction,” his note was “a real proposal for joint research.” Roorda finally replied, proposing coffee. “I get a lot of e-mails suggesting what I should research,” Roorda told me, of the time it took him to respond.

In the children’s novel “The Midnight Fox,” by Betsy Byars, the main character daydreams about digging in his back yard and coming across a “brand-new color.” A friend of mine remembers being captivated by this scene, and trying to picture the color. “I felt like I could conceive of it, but I couldn’t see it,” she said. The eighteenth-century Scottish philosopher David Hume considered at length whether a person who had seen every shade of blue except for one would be able to picture that one un-experienced shade; he concluded that the answer was yes. In my youth, I spent an afternoon wondering if I would have been able to imagine the fluorescent yellow of highlighter markers if I’d never seen it.

When I first read about Ng and Roorda’s work, I tried to visualize what it would mean for there to be a new color. Where would it go in a color wheel? If you think of color as a property of a specific wavelength of light—which is how I thought of it—then you run into the impossibility of there being a “new” visible wavelength. As humans, we can see wavelengths from roughly 380 nanometres (which looks violet to us) to about 750 nm. (which looks red). Wavelengths shorter than 380 nm., which we’d call ultraviolet, are invisible to us (but not to bees or hummingbirds), as are wavelengths longer than 750 nm., which we refer to as infrared (and which snakes and salmon can perceive). The “greenest green” that Ng had in mind was neither ultraviolet nor infrared. It was not a new wavelength at all. If I wanted to picture this green, or at least try to, I would first have to understand that even the old familiar colors are much more complex than a particular wavelength of light.

by Rivka Galchen, New Yorker | Read more:
Image: Zach Lieberman

Jacques Villon,The Philosopher, 1930
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