The Conversation: Two of the most famous experiments in psychology, the Stanford prison experiment and Stanley Milgram’s obedience studies, have been called a sham, a lie and a fraud.

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Two of the most famous experiments in psychology, the Stanford prison experiment and Stanley Milgram’s obedience studies, have been called a sham, a lie and a fraud.

Retraction Watch, a site that tracks withdrawn research papers, has hosted an argument for retracting the Stanford paper. Psychologists have even been told that almost everything they thought they knew about Milgram is wrong.

Yet interest has not faded. This month, Netflix released six episodes of The New Stanford Prison Experiment, putting the 1971 study back in the spotlight. Why do these much-criticised experiments keep drawing us back?

Part of the answer is how strong the original findings sounded. They came from what is often called the golden age of American social psychology, roughly the 1950s to the early 1970s. Researchers in this period ran dramatic experiments on how groups and authority shape what ordinary people do.

In the 1950s, the psychologist Solomon Asch asked students to match the length of a line to one of three others. When a room of actors all gave the same wrong answer, many of the real participants went along with them – at least some of the time.

In the early 1960s at Yale University, Stanley Milgram told volunteers they were helping with a study of memory and learning. They were asked to give electric shocks – rising to a level labelled dangerous – to a man in another room whenever he got a question wrong.

The shocks were fake and the man was an actor, but the participants did not know that. In the experiment’s initial version, 65% of them went all the way to the top of the scale when a man in a lab coat told them to continue.

In the late 1960s, the psychologists John Darley and Bibb Latané studied why people so often fail to help in an emergency. In one experiment, volunteers heard over an intercom what sounded like another participant having a seizure. The more people they believed could also hear, the less likely each one was to go for help.

Philip Zimbardo, a Stanford University psychologist who later became president of the American Psychological Association, was the last of these big names. In August 1971, he turned the basement of Stanford’s psychology department into a mock prison. He randomly assigned 24 male students to play guards or prisoners in what was meant to be a two-week study.

He had to stop it after just six days, however, because some of the guards had become overly cruel and some of the prisoners had broken down.

American social psychologist, Philip Zimbardo.
American social psychologist, Philip Zimbardo. CTK/Alamy

The critics

In a 2019 analysis of the Stanford archive, the French researcher Thibault Le Texier argued that Zimbardo’s team gave the guards instructions on how to behave, so they were not acting spontaneously. Some prisoners later said they had exaggerated their distress. The study also began as a student project.

Milgram’s work has also been attacked. One analysis argued that he manufactured obedience in the lab rather than discovered it. And psychologists, writing for The Conversation, have pointed out that across all versions of his experiment, more people disobeyed than obeyed.

Some of this criticism, though, is not new, because the researchers disclosed the facts themselves. Zimbardo’s 2007 bestseller, The Lucifer Effect, credits his students with the original idea. It also describes how he acted as the prison’s “superintendent” and briefed and coached the guards.

The same goes for Milgram. He published the results of many of the variations himself, and noted that obedience fell sharply in some of them. However, those were variations that bore little resemblance to the original experiment setup.

The harder test is the alternative explanation. Alex Haslam of the University of Queensland and Stephen Reicher of the University of St Andrews, both social psychologists, have argued for years that obedience alone cannot explain what happened. In 2002, they ran the BBC prison study, a televised re-run of Zimbardo’s idea, in which guards did not spontaneously turn cruel.

They suggest that participants believed in the scientific cause and chose to carry on – an idea they call “engaged followership”. Their explanation has numerous critics, however, who say they overlook evidence from what was said and done during Milgram’s and Zimbardo’s original sessions.

Flawed though their experiments may have been by today’s ethical and methodological standards, Zimbardo and Milgram did chance upon something grave and important in human nature. They confronted their participants with a clear moral dilemma: will you choose evil, or will you choose good? And they witnessed ordinary person after ordinary person freely – albeit agonisingly – choosing evil.

That profound and deeply disturbing message is why people keep coming back to these decades-old studies.

Nothing that Zimbardo, Milgram, their most committed supporters or their fiercest critics have said comes close to fully explaining why ordinary people in their labs tended to choose evil when they could, with no consequence, choose good.

Of course, many of the pressures that made that fateful choice difficult are now known. But no amount of pressure accounts for the Stanford guards choosing to brutalise their fellows, or Milgram’s participants choosing to give yet another electric shock, when they could have freely chosen otherwise.

Zimbardo, Milgram and the other studies reveal something monstrous about ordinary human beings – about us all – while remaining elusive, enigmatic, almost mysterious. Until we understand why, as Milgram’s experimenter told hesitant participants: “The experiment requires that you continue.”

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euobserver: Digital panopticon … be prepared!

epa06328432 A general view of employees working at the new Amazon Logistic and Fulfillment Center in Dortmund, Germany, 14 November 2017. The Fulfillment Center is reportedly one of Amazon's newest and most modern European facilities and said to create hundreds of new jobs in Dortmund.  EPA/FRIEDEMANN VOGEL

Amazon’s 42,000 square metre warehouse in Dortmund. Workers complain about unrealistic algorithm-set goals, ignoring the real working conditions (Source: EPA/FRIEDEMANN VOGEL)

Europe today

Digital panopticon: ‘When you work faster, you have to work even faster’ Amazon workers tell MEPs on AI work surveillance

By Zuzanna Stawiska

Brussels

28 October 2026 17:56

The European Parliament’s employment committee has highlighted the need for regulating automated control of workers after visiting Amazon warehouses in Germany and Poland this week.

Seven of the committee MEPs visited Amazon warehouses employing some 5,000 workers on Monday and Tuesday (26-27 October) ahead of the Commission’s Quality Jobs Act proposal expected in December.

The trip follows the committee’s hearing on working conditions in Amazon in January, where workers raised concerns about efficiency goals, safety, and surveillance using AI tools, which may be regulated more rigorously as a part of the upcoming act.

According to a 2023 survey by UNI Europa, a labour union federation, about a half of Amazon’s employees said their work had a negative impact on their mental and physical health.

Read more

Unions rally against new ‘EU Inc’ race-to-bottom on labour laws and pay

Workers’ progress throughout the day is usually watched through security cameras, but also the work badges scanned in check points in various locations in the warehouse, and scanning devices used to identify products.

In the city of Sosnowiec, home to one of Amazon’s Polish warehouses, employees are overworked by “constant pressure of being judged, which is very hard to cope with mentally,” Agata Wypiór, recently-named vice secretary of Amazon’s European Works Council and Solidarność union leader told EUobserver.

Leaving worker management and performance monitoring to algorithms means “these processes become almost invisible,” Li Andersson, head of the delegation, told EUobserver.

“The way the workers describe it, it sounds like a digital panopticon: when you work faster you have to work even faster.“

Workers themselves often do not know what data is collected on them and how it is being used to set productivity targets, Anderssen highlighted.

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The Harvard Gazette: Children Are Left Out of Medical AI. A New Method Could Help.

  1. News & Events
X-ray image of an intubated infant
Caption: X-ray included in the study of an infant with a breathing tube. Image: Adapted from Rao et al., Nature Biomedical Engineering (2026), CC BY 4.0.

Children Are Left Out of Medical AI. A New Method Could Help.

Adult radiology models can be adapted for newborns without data leaving hospitals

Research 3 min read

By LAURA CASTAÑÓN October 13, 2026

At a glance

  • Researchers adapted an adult X-ray AI model for newborns with data from 30 hospitals, using a method designed to keep each hospital’s data in place.
  • The new model outperformed adult models trained on pediatric data from a single hospital at 29 of 30 sites, even when tested on that hospital’s own images.
  • This approach could be generalized to adapt other adult-trained AI models for use in children without needing large amounts of pediatric data to be added to public imaging datasets.

In the field of radiology, AI models have the potential to improve imaging analysis, speed up diagnoses, and catch errors that might otherwise be missed. But the vast majority of these models are trained on adult data and don’t translate well to infants and children, keeping these advances out of reach of neonatal and pediatric health.

“Because it’s so much harder to get data for children, this transformative technology is disproportionately being developed to help adults,” said Vishwanatha Rao, a member of Pranav Rajpurkar’s biomedical informatics lab at Harvard Medical School. “Children are being left behind.”

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A large part of the reason for the gap is that medical records on newborns and children are subject to strict privacy regulations and tend to remain within the institution where the child is a patient, leaving data less accessible to train robust AI models. According to Rao and colleagues, children represent less than 1 percent of public medical imaging datasets.

Rao led and is co-first author on a new study, published Oct. 13 in Nature Biomedical Engineering, showing that models trained on adult radiographs can be adapted for infants using data from multiple hospitals without sensitive information ever needing to leave each institution. The model travels, but the data stays in-house.

The team believes its proof-of-principle approach could be extended to adapt other adult-trained AI models for pediatric use, addressing critical gaps in the deployment of pediatric medical AI.

“Our goal is to figure out how to make medical AI models work for everyone, including vulnerable populations where data can’t easily be shared,” said senior author Rajpurkar, associate professor of biomedical informatics in the Blavatnik Institute at HMS. “Now we’ve come up with a method which would allow for every institution to keep its data within its walls.”

Training sequentially

The researchers started with a model that had been trained on adult data to assess whether breathing tubes have been placed correctly. Breathing tubes, or endotracheal tubes, are crucial for treating respiratory issues, and there is little margin for error, especially in newborns.

Studies have shown that AI models can quickly flag potential issues and shorten the time it takes for radiologists to review and correct tube placement. Multiple AI tools have already received FDA clearance for this task in adults, but none of them are cleared for infants.

Rajpurkar and colleagues collected 2,965 chest X-rays from 30 neonatal intensive care units across 20 countries and territories. To simulate a scenario in which the data never leaves the hospital, the researchers trained the model sequentially on each institution’s data.

Take the next step in your career at Harvard Medical School by applying for a master's degree, learn more

Despite differences in image quality and characteristics, the new model outperformed adult models trained on pediatric data from a single hospital at 29 of 30 sites, even when tested on that hospital’s own images, which the new model had never seen.

The fully trained model was able to identify the location of the tip of the endotracheal tube — used to gauge whether the tube is too shallow or too deep — with an average error of 0.67 cm. Existing models adapted to children with data from a single institution averaged errors of 1.29 cm, and adult models were off by an average of 4.30 cm.

“We tested the model on a hospital it had never seen before, and it did better than a model trained on scans from that specific hospital — that’s a pretty powerful result,” said Rao, who is an MD-PhD student at the University of Pennsylvania. “And compared to the original adult model, it’s leaps and bounds better.”

Medical AI for all

Only 17 percent of FDA-authorized AI medical devices are labeled for use in children. While this particular model was trained on endotracheal tube placement, the approach could be generalized to adapt other adult models for pediatric use, the researchers said.

“This is a general framework that shows a cheap, privacy-preserving approach to take advantage of existing adult information and get it to work on children,” Rao said. “It could usher in a whole new generation of AI models that work for kids, adapted through this broad methodology.”

The method isn’t limited to pediatrics, either. The same framework could potentially be applied to any patient population that is underrepresented in AI training data.

“A lot of what research is meant to accomplish is showing that something is possible,” Rajpurkar said. “We’ve shown there’s a system by which you can tune these models without sensitive data leaving a hospital.”

Authorship, funding, disclosures

Emma Chen and Agustina Saenz are co-first authors of the study. Additional authors include Oishi Banerjee, Henrik Marklund, Lucas Bijnens, Sung Eun Kim, Evan Zucker, Susan Shelmerdine, Jeremy Palacio, Kent Ryan Kleinschmidt, Sathvik Suryadevara, Sri Sai Dinesh Jaliparthi, Jiaxi Lu, Rithvik Akula, Mario Scala, Julian F. Niedermair, Nikolaus Stranger, Sebastian Tschauner, Georg M. Schmölzer, Maria Jose Veloza Vega, Juan Sebastián Osorio Valencia, Oscar Jaramillo Robledo, Oscar Julian López Uribe, Saif Afat, Thomas Küstner, Soroosh Tayebi Arasteh, Daniel Truhn, Kelsey L. Pomykala, Jens Kleesiek, Naela Himayati Afifah, Rozan M. Irfan, Reza Shahriarirad, Amirhossein Erfani, Israel Amirav, Moria Be’er, Yasuhito Mitsuyama, Daiju Ueda, Alain S. Abi-Ghanem, Safaa Al Zakleet, Mossad Abdelhak Shaban Mohamed, Wan Irfan Bin W. Mustapha, Naila Nizami, Rafeah Khan, Khalid Al-Kharazi, Zafar Iqbal, Abdullah Al Shahrani, Amna Kashgari, Tijana Prodanovic, Nikola Prodanovic, Lim Shi Wei Desmond, James Thomas Patrick Decourcy Hallinan, Phumza Nongena, Melissa Louise Cooke, Montserrat Bret-Zurita, Almudena Alonso-Ojembarrena, Alexandra Nemes, Yung-Chieh Lin, Wei-Ting Lin, Wen-Hui Fang, Chin Lin, Atchara Mahayosnond, Sira Sriswasdi, Piyapong Khumrin, Suphakris Tanmuk, Didem Arman, Serdar Cömert, Serdar Alan, Umit Ayse Tandircioglu, David Andrew Mong, Esther Chung, Michael Sadler, Morgan P. McBee, and Richard H. Jones.

This work was supported by the Biswas Family Foundation Transformative Computational Biology Grant in collaboration with the Milken Institute. Bijnens was supported by Junior Orsi and Barco.

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Mario Nawfal on X: Israeli Arab party leader FIRES BACK at Likud’s claims of a “stolen” election

Israeli Arab party leader FIRES BACK at Likud’s claims of a “stolen” election

Joint List leader Ahmad Tibi slammed Netanyahu’s Likud party over allegations of election fraud, calling them the excuses of sore losers.

“There were no irregularities in the elections. The accusations made by the Likud are merely the rhetoric of the defeated.”

Tibi accused Likud of trying to discredit Arab voters as his alliance celebrated what he called a sweeping victory.

The Joint List is projected to take 12 seats, with Ra’am claiming another 7, giving Arab-led parties 19 of 120 Knesset seats.

Likud cries foul as Arab parties claim a major win.

Source: Al Jazeera / Writer: Marie

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CRUX: Richard Dawkins On God vs AI: Is Technology Changing Human Beliefs?

11,479 views Oct 27, 2026 #richarddawkins#elonmusk#artificialintelligence

Renowned evolutionary biologist and bestselling author Richard Dawkins explores the intersection of God, religion, artificial intelligence, and the future of humanity. In this thought-provoking discussion, Dawkins examines the relationship between science and faith, the evolution of human intelligence, and the growing influence of AI technology. From Elon Musk’s role in artificial intelligence to questions about consciousness, atheism, and the existence of God, Richard Dawkins offers his perspective on the challenges posed by technological advancement. Watch Richard Dawkins discuss AI, Elon Musk, religion, evolution, and the future of human civilization as science and technology continue to transform our world.

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Oct 23, 2026 #WWII#WorldWarTwo#Churchill

In the darkest hour of World War II, Britain was being strangled. German U-boats were sinking merchant ships faster than British shipyards could build them. Food, oil, and war supplies were vanishing to the bottom of the Atlantic every single week. And just a few miles off Britain’s western coast sat three magnificent deep-water harbors that could have changed everything. Cobh, Berehaven, and Lough Swilly, the so-called Treaty Ports, had belonged to the Royal Navy for over a century. They were perfect bases to refuel destroyers, launch patrol aircraft, and shelter convoys. But in 1938, Prime Minister Neville Chamberlain gave them back to Ireland, with no guarantee they could ever be used again. By 1940, Winston Churchill was Prime Minister of a country fighting for its life, and the man who had once called those ports “the sentinel towers of the western approaches” could only watch as his sailors drowned in waters he was forbidden to patrol. So why didn’t Churchill just take them back? He had the ships. He had the troops. He had the ruthlessness, the same ruthlessness that destroyed the French fleet at Mers-el-Kébir and leveled German cities from the air. He threatened Dublin openly. He had Montgomery drawing up invasion maps. He gave speeches in the Commons practically begging for an excuse to act. And yet he never pulled the trigger.

This video uncovers the real reasons behind one of the most puzzling decisions of the Second World War. We trace the story from the 1921 Anglo-Irish Treaty through the shocking 1938 handover, into the catastrophic U-boat Happy Time of 1940, through Churchill’s secret unification offer to Éamon de Valera, all the way to Churchill’s bitter 1945 victory speech and de Valera’s legendary reply. Along the way we uncover the hidden cooperation between neutral Ireland and the Allies that Churchill never dared admit publicly, the twenty million Irish Americans whose votes could have killed Lend-Lease overnight, the IRA plots to welcome Hitler into Ireland, and the chilling German invasion plan called Operation Green. What emerges is a masterclass in strategic restraint. Churchill, the lion of empire, calculated that the quiet humiliation of a defiant neutral Ireland was more valuable than the three harbors he desperately wanted. He understood that invading Ireland would have handed Hitler a propaganda gift, de Valera a martyr’s halo, and the American isolationists their best argument against entering the war. The decision not to seize was itself the strategy. And it worked. If this story made you see the Second World War in a new light, hit the like button, drop a comment telling us what surprised you most, and subscribe for more deep dives into the forgotten decisions and overlooked turning points of history. Topics covered include the Anglo-Irish Treaty, the Irish Treaty Ports, Winston Churchill and Éamon de Valera, Neville Chamberlain, the Battle of the Atlantic, German U-boat wolf packs, Admiral Karl Dönitz, the fall of France, Operation Green, Plan W, the Donegal Corridor, Irish neutrality in World War II, the Emergency in Ireland, Lend-Lease, Franklin Roosevelt, the Blacksod Point weather report and D-Day, Western Approaches Command, and the long shadow of partition in Ireland. Sources

  • Robert Fisk, In Time of War: Ireland, Ulster and the Price of Neutrality
  • Tim Pat Coogan, De Valera: Long Fellow, Long Shadow
  • Winston Churchill, The Second World War
  • Clair Wills, That Neutral Island
  • Bryce Evans, Ireland During the Second World War
  • Michael Kennedy, Guarding Neutral Ireland
  • T. Ryle Dwyer, Behind the Green Curtain
  • Karen Garner, Friends and Enemies: The Allies and Neutral Ireland in WWII
  • Ian S. Wood, Britain, Ireland and the Second World War
  • Documents on Irish Foreign Policy, Volumes 6 and 7
  • Foreign Relations of the United States, 1940 and 1941
  • Imperial War Museum archives
  • Naval History Net, Royal Navy Day by Day
  • The Churchill Project, Hillsdale College
  • History Ireland magazine
  • Finest Hour, journal of the International Churchill Society

#WWII#WorldWarTwo#Churchill#WinstonChurchill#DeValera#Ireland#IrishHistory#BattleOfTheAtlantic#Uboats#RoyalNavy#WW2History#SecondWorldWar#BritishHistory#TreatyPorts#IrishNeutrality#MilitaryHistory#WarHistory#Chamberlain#Cobh#Berehaven#LoughSwilly#OperationGreen#PlanW#DonegalCorridor#ForgottenHistory#HistoryDocumentary#WW2Documentary#AtlanticWar#ConvoyWar#BritishEmpire

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AI Could Destroy the World. Should We Still Invest? THREAT TO HUMANITY

Oct 27, 2026

Watch Can We Agree: https://www.youtube.com/show/VLPLArM1… Would you invest in a company that warns its own technology could threaten humanity? Anthropic, the company behind the AI model Claude, has filed to go public—and its extraordinary IPO prospectus contains more than 90 pages of potential risks, including warnings that artificial intelligence could pose catastrophic or even existential threats to humanity. Michael Smerconish speaks with retired Admiral James Stavridis, former Supreme Allied Commander of NATO, about the promises and dangers of artificial intelligence, the urgent need for government regulation, and the growing conflict between AI developers and the U.S. military. Anthropic’s filing paints two dramatically different futures. In one, AI helps cure cancer and Alzheimer’s disease, accelerates scientific breakthroughs, and transforms government services. In another, increasingly autonomous AI systems manipulate humans, resist shutdown, and potentially escape human control. Stavridis, who explored the future of artificial intelligence in his novel 2054, says the technology’s accelerating development demands thoughtful government oversight. But he also warns against regulating AI so aggressively that society forfeits its extraordinary potential. The conversation also examines Anthropic’s dispute with the Pentagon over autonomous weapons and mass surveillance. When a private technology company refuses military applications of its AI, who should have the final say? And with Anthropic openly acknowledging potentially catastrophic risks, what responsibility do investors, policymakers, and the public have in determining AI’s future? Stavridis also discusses the possibility that AI systems may ultimately reflect the values and flaws of the humans who create them. Join the conversation in the comments. Vote on today’s poll and subscribe to the daily newsletter at http://www.smerconish.com

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Axios: Twin victory speeches

Twin victory speeches
 
Gadi Eisenkot, leader of the Yashar party, waves an Israeli flag onstage following the release of the first exit poll in Israel’s general election in Tel Aviv last night. Photo: Ariel Schalit/APAxios’ Barak Ravid reports from Tel Aviv:

Prime Minister Benjamin Netanyahu’s far-right coalition was running nearly even with Gadi Eisenkot’s opposition bloc as vote counting continued today — but both are short of a 61-seat majority.

Why it matters: Political stalemate is the most likely outcome of yesterday’s historic election, with Netanyahu weakened but neither side having a clear path to forming a coalition government. Weeks of negotiating could lie ahead. Arab parties are poised to win 18 to 19 seats in what would be an unprecedented electoral achievement.

Theoretically, Eisenkot’s bloc could try to swear in a minority government supported by the two Arab parties. But that looks unlikely.

📊 State of play: A close outcome could leave the country in a state of limbo, with Netanyahu likely staying on as a caretaker prime minister at the helm of the executive branch and the opposition led by Eisenkot controlling the Knesset.

That scenario could last until new elections, possibly as early as April.

The two sides could try to break the deadlock by forming a unity government between Netanyahu and Eisenkot. But that’s improbable, since none of the opposition parties will agree to sit in a Netanyahu-led government.Israeli Prime Minister Benjamin Netanyahu speaks at an election-night rally in Jerusalem. Photo: Jalaa Marey/AFP via Getty Images

🔎 Zoom in: Eisenkot claimed victory in a speech after midnight Israeli time. He said if Netanyahu was a “decent leader,” he’d leave the political stage after the public voted for change.Eisenkot alluded to the possibility that the prime minister would launch military action before a new government is seated. “Netanyahu, don’t dare use Israel’s security for your political needs,” Eisenkot said.

After 3 a.m. Israeli time, Netanyahu took the stage and also claimed victory:

“We are still waiting for the official election results. Likud is the largest party in Israel. The right-wing bloc has a clear, decisive majority among the Zionist public and among the Jewish population as a whole.” Share this story.
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The Rundown AI: Anthropic starts developing its own drugs

💊 Anthropic starts developing its own drugs
Image source: Anthropic
The Rundown: Anthropic shared early results with its drug-development partners and revealed it’s now running its own drug discovery programs, including buying Mithril Medicine, a solo-founder biotech whose Claude-assisted muscular dystrophy candidate could reach human trials as early as late 2028.
The details:
The candidate showed promise in mice within 18 months, with Claude helping solo founder Cody Tranbarger juggle contracts and tests at 11 outside labs.Tranbarger also turned out to be “Professor Oak,” a biotech account run pseudonymously on X for six years, and calls the setup a “Pipeline-in-a-Person.”At Enveda, Claude wrote a first draft of a key regulatory filing in 4 hours vs. ~3 months by hand, and also flagged seven batch-record issues humans missed.In another case, three of roughly 35K antibodies Claude designed for Divergence Labs appeared to beat today’s main drug at unhooking allergy triggers from cells.This week’s IPO filing pitched a global pharma market expected to top $2T this year, but Anthropic warned its own drug bets “may never generate revenue.”
Why it matters: Dario Amodei said in August to expect “early glimmers” from Anthropic’s biology push in the coming months, and we’re seeing the groundwork for that. With Anthropic also running its own wet lab, and its IPO filing saying Claude can operate gear like microscopes, the pieces for AI’s hands-on science are falling into place fast.
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Futurism: It Appears That the AI Bubble Has Just Burst in China

It Appears That the AI Bubble Has Just Burst in China

“And now we see the bubble bursting.”

By Frank Landymore

Published Oct 27, 2026 10:57 AM EDT

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As economists in the rest of the world look at the billions being poured into the AI industry with their hands over their eyes, the fate of China’s AI industry may be a sign of things to come.

A report from Reuters suggests that the AI bubble in China “has already burst.” Or it might be more apt to say that it shriveled like a rapidly deflating balloon: over the past four months, Reuters notes, the country’s STAR50 index of AI and semiconductor companies collapsed by 40 percent, wiping out $480 billion in market value. That is not a typo.

“The stock market later evolved into a speculative crazy bull,” Beijing-based fund manager Dong Baozhen told Reuters. “And now we see the bubble bursting.”

Shares of Unitree, China’s buzzy robotics company, have halved since the company went public in a much-hyped IPO in August, the reporting noted. The chipmaker CXMT, meanwhile, has lost more than a quarter of its value over the past month.

The vicissitudes of the stock market haven’t completely dampened AI investors’ spirits, though. DeepSeek, one of China’s top AI companies, recently raised $15 billion in one of the largest funding rounds in the country’s history, Bloomberg reported. The outlet also noted that Huawei clinched a $2.3 billion loan from Chinese banks to spend on more AI chips.

The conditions in China, of course, are different than elsewhere in the world. China faces constant efforts from the US to ice it out of global competition, with tariffs and the US considering an outright ban on Chinese companies supplying equipment to data centers, such as Zhongji Innolight, whose optical transceivers are critical for facilitating the light-speed transfers of the epic amounts of data that AI requires. It’s worth noting that the role of the economic hostility by the US and other western countries in the Chinese market downturn could be being understated, with the downturn as much a consequence of China being blocked from selling its AI products overseas as much as it is of market arrogance.

Still, the scale of money being poured into AI and AI-related industries — with AI stocks taking up some 42 percent of China’s market capitalization, according to Goldman Sachs  — isn’t too dissimilar to what’s happening in Western economies, where the obvious lack of a return of investment becomes harder to ignore. Anthropic’s recent disclosure in its IPO filing of a staggering $80 billion loss — and plans to spend another $1 trillion on data centers over the next decade — will only further fuel fears that even the industry’s top players are still far from being profitable.

According to Reuters, state-backed investors sold into market rallies, or periods of rapid gains, to keep those gains in check, as part of a push by the government to dampen volatility. However intentioned that tactic may have been, it couldn’t dress up the fact that the demand for AI products just isn’t there yet.

More on AI: New Analysis Finds Signs the AI Bubble Is About to Blow

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Frank Landymore

Contributing Writer

I’m a tech and science correspondent for Futurism, where I’m particularly interested in astrophysics, the business and ethics of artificial intelligence and automation, and the environment.

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