AI

In comedy of errors, men accused of wiping gov databases turned to an AI tool

AI, Biz & IT, contractors, courts, data theft / Mike M. / December 4, 2025

Two sibling contractors convicted a decade ago for hacking into US State Department systems have once again been charged, this time for a comically hamfisted attempt to steal and destroy government records just minutes after being fired from their contractor jobs.

The Department of Justice on Thursday said that Muneeb Akhter and Sohaib Akhter, both 34, of Alexandria, Virginia, deleted databases and documents maintained and belonging to three government agencies. The brothers were federal contractors working for an undisclosed company in Washington, DC, that provides software and services to 45 US agencies. Prosecutors said the men coordinated the crimes and began carrying them out just minutes after being fired.

Using AI to cover up an alleged crime—what could go wrong?

On February 18 at roughly 4: 55 pm, the men were fired from the company, according to an indictment unsealed on Thursday. Five minutes later, they allegedly began trying to access their employer’s system and access federal government databases. By then, access to one of the brothers’ accounts had already been terminated. The other brother, however, allegedly accessed a government agency’s database stored on the employer’s server and issued commands to prevent other users from connecting or making changes to the database. Then, prosecutors said, he issued a command to delete 96 databases, many of which contained sensitive investigative files and records related to Freedom of Information Act matters.

Despite their brazen attempt to steal and destroy information from multiple government agencies, the men lacked knowledge of the database commands needed to cover up their alleged crimes. So they allegedly did what many amateurs do: turned to an AI chat tool.

One minute after deleting Department of Homeland Security information, Muneep Akhter allegedly asked an AI tool “how do i clear system logs from SQL servers after deleting databases.” Shortly afterward, he queried the tool “how do you clear all event and application logs from Microsoft windows server 2012,” prosecutors said.

The indictment provides enough details of the databases wiped and information stolen to indicate that the brothers’ attempts to cover their tracks failed. It’s unclear whether the apparent failure was due to the AI tool providing inadequate instructions or the men failing to follow them correctly. Prosecutors say they also obtained records of discussions between the men in the hours or days following, in which they discussed removing incriminating evidence from their homes. Three days later, the men allegedly wiped their employer-issued laptops by reinstalling the operating system.

In comedy of errors, men accused of wiping gov databases turned to an AI tool Read More »

Researchers find what makes AI chatbots politically persuasive

AI, Behavioral science, chat gpt, Computer science, grok, Human behavior, large language models, Science / Tim Belzer / December 4, 2025

A massive study of political persuasion shows AIs have, at best, a weak effect.

Roughly two years ago, Sam Altman tweeted that AI systems would be capable of superhuman persuasion well before achieving general intelligence—a prediction that raised concerns about the influence AI could have over democratic elections.

To see if conversational large language models can really sway political views of the public, scientists at the UK AI Security Institute, MIT, Stanford, Carnegie Mellon, and many other institutions performed by far the largest study on AI persuasiveness to date, involving nearly 80,000 participants in the UK. It turned out political AI chatbots fell far short of superhuman persuasiveness, but the study raises some more nuanced issues about our interactions with AI.

AI dystopias

The public debate about the impact AI has on politics has largely revolved around notions drawn from dystopian sci-fi. Large language models have access to essentially every fact and story ever published about any issue or candidate. They have processed information from books on psychology, negotiations, and human manipulation. They can rely on absurdly high computing power in huge data centers worldwide. On top of that, they can often access tons of personal information about individual users thanks to hundreds upon hundreds of online interactions at their disposal.

Talking to a powerful AI system is basically interacting with an intelligence that knows everything about everything, as well as almost everything about you. When viewed this way, LLMs can indeed appear kind of scary. The goal of this new gargantuan AI persuasiveness study was to break such scary visions down into their constituent pieces and see if they actually hold water.

The team examined 19 LLMs, including the most powerful ones like three different versions of ChatGPT and xAI’s Grok-3 beta, along with a range of smaller, open source models. The AIs were asked to advocate for or against specific stances on 707 political issues selected by the team. The advocacy was done by engaging in short conversations with paid participants enlisted through a crowdsourcing platform. Each participant had to rate their agreement with a specific stance on an assigned political issue on a scale from 1 to 100 both before and after talking to the AI.

Scientists measured persuasiveness as the difference between the before and after agreement ratings. A control group had conversations on the same issue with the same AI models—but those models were not asked to persuade them.

“We didn’t just want to test how persuasive the AI was—we also wanted to see what makes it persuasive,” says Chris Summerfield, a research director at the UK AI Security Institute and co-author of the study. As the researchers tested various persuasion strategies, the idea of AIs having “superhuman persuasion” skills crumbled.

Persuasion levers

The first pillar to crack was the notion that persuasiveness should increase with the scale of the model. It turned out that huge AI systems like ChatGPT or Grok-3 beta do have an edge over small-scale models, but that edge is relatively tiny. The factor that proved more important than scale was the kind of post-training AI models received. It was more effective to have the models learn from a limited database of successful persuasion dialogues and have them mimic the patterns extracted from them. This worked far better than adding billions of parameters and sheer computing power.

This approach could be combined with reward modeling, where a separate AI scored candidate replies for their persuasiveness and selected the top-scoring one to give to the user. When the two were used together, the gap between large-scale and small-scale models was essentially closed. “With persuasion post-training like this we matched the Chat GPT-4o persuasion performance with a model we trained on a laptop,” says Kobi Hackenburg, a researcher at the UK AI Security Institute and co-author of the study.

The next dystopian idea to fall was the power of using personal data. To this end, the team compared the persuasion scores achieved when models were given information about the participants’ political views beforehand and when they lacked this data. Going one step further, scientists also tested whether persuasiveness increased when the AI knew the participants’ gender, age, political ideology, or party affiliation. Just like with model scale, the effects of personalized messaging created based on such data were measurable but very small.

Finally, the last idea that didn’t hold up was AI’s potential mastery of using advanced psychological manipulation tactics. Scientists explicitly prompted the AIs to use techniques like moral reframing, where you present your arguments using the audience’s own moral values. They also tried deep canvassing, where you hold extended empathetic conversations with people to nudge them to reflect on and eventually shift their views.

The resulting persuasiveness was compared with that achieved when the same models were prompted to use facts and evidence to back their claims or just to be as persuasive as they could without specifying any persuasion methods to use. I turned out using lots of facts and evidence was the clear winner, and came in just slightly ahead of the baseline approach where persuasion strategy was not specified. Using all sorts of psychological trickery actually made the performance significantly worse.

Overall, AI models changed the participants’ agreement ratings by 9.4 percent on average compared to the control group. The best performing mainstream AI model was Chat GPT 4o, which scored nearly 12 percent followed by GPT 4.5 with 10.51 percent, and Grok-3 with 9.05 percent. For context, static political ads like written manifestos had a persuasion effect of roughly 6.1 percent. The conversational AIs were roughly 40–50 percent more convincing than these ads, but that’s hardly “superhuman.”

While the study managed to undercut some of the common dystopian AI concerns, it highlighted a few new issues.

Convincing inaccuracies

While the winning “facts and evidence” strategy looked good at first, the AIs had some issues with implementing it. When the team noticed that increasing the information density of dialogues made the AIs more persuasive, they started prompting the models to increase it further. They noticed that, as the AIs used more factual statements, they also became less accurate—they basically started misrepresenting things or making stuff up more often.

Hackenburg and his colleagues note that we can’t say if the effect we see here is causation or correlation—whether the AIs are becoming more convincing because they misrepresent the facts or whether spitting out inaccurate statements is a byproduct of asking them to make more factual statements.

The finding that the computing power needed to make an AI model politically persuasive is relatively low is also a mixed bag. It pushes back against the vision that only a handful of powerful actors will have access to a persuasive AI that can potentially sway public opinion in their favor. At the same time, the realization that everybody can run an AI like that on a laptop creates its own concerns. “Persuasion is a route to power and influence—it’s what we do when we want to win elections or broke a multi-million-dollar deal,” Summerfield says. “But many forms of misuse of AI might involve persuasion. Think about fraud or scams, radicalization, or grooming. All these involve persuasion.”

But perhaps the most important question mark in the study is the motivation behind the rather high participant engagement, which was needed for the high persuasion scores. After all, even the most persuasive AI can’t move you when you just close the chat window.

People in Hackenburg’s experiments were told that they would be talking to the AI and that the AI would try to persuade them. To get paid, a participant only had to go through two turns of dialogue (they were limited to no more than 10). The average conversation length was seven turns, which seemed a bit surprising given how far beyond the minimum requirement most people went. Most people just roll their eyes and disconnect when they realize they are talking with a chatbot.

Would Hackenburg’s study participants remain so eager to engage in political disputes with random chatbots on the Internet in their free time if there was no money on the table? “It’s unclear how our results would generalize to a real-world context,” Hackenburg says.

Science, 2025. DOI: 10.1126/science.aea3884

Jacek Krywko is a freelance science and technology writer who covers space exploration, artificial intelligence research, computer science, and all sorts of engineering wizardry.

Researchers find what makes AI chatbots politically persuasive Read More »

ChatGPT hyped up violent stalker who believed he was “God’s assassin,” DOJ says

AI, chatgpt, cyberstalking, Instagram, openai, Policy, Spotify, tiktok / Tim Belzer / December 4, 2025

A stalker’s “best friend”

Podcaster faces up to 70 years and a $3.5 million fine for ChatGPT-linked stalking.

ChatGPT allegedly validated the worst impulses of a wannabe influencer accused of stalking more than 10 women at boutique gyms, where the chatbot supposedly claimed he’d meet the “wife type.”

In a press release on Tuesday, the Department of Justice confirmed that 31-year-old Brett Michael Dadig currently remains in custody after being charged with cyberstalking, interstate stalking, and making interstate threats. He now faces a maximum sentence of up to 70 years in prison that could be coupled with “a fine of up to $3.5 million,” the DOJ said.

The podcaster—who primarily posted about “his desire to find a wife and his interactions with women”—allegedly harassed and sometimes even doxxed his victims through his videos on platforms including Instagram, Spotify, and TikTok. Over time, his videos and podcasts documented his intense desire to start a family, which was frustrated by his “anger towards women,” whom he claimed were “all the same from fucking 18 to fucking 40 to fucking 90” and “trash.”

404 Media surfaced the case, noting that OpenAI’s scramble to tweak ChatGPT to be less sycophantic came before Dadig’s alleged attacks—suggesting the updates weren’t enough to prevent the harmful validation. On his podcasts, Dadig described ChatGPT as his “best friend” and “therapist,” the indictment said. He claimed the chatbot encouraged him to post about the women he’s accused of harassing in order to generate haters to better monetize his content, as well as to catch the attention of his “future wife.”

“People are literally organizing around your name, good or bad, which is the definition of relevance,” ChatGPT’s output said. Playing to Dadig’s Christian faith, ChatGPT’s outputs also claimed it was “God’s plan for him was to build a ‘platform’ and to ‘stand out when most people water themselves down,’” the indictment said, urging that the “haters” were “sharpening him and ‘building a voice in you that can’t be ignored.’”

The chatbot also apparently prodded Dadig to continue posting messages that the DOJ alleged threatened violence, like breaking women’s jaws and fingers (posted to Spotify), as well as victims’ lives, like posting “y’all wanna see a dead body?” in reference to one named victim on Instagram.

He also threatened to burn down gyms where some of his victims worked, while claiming to be “God’s assassin” intent on sending “cunts” to “hell.” At least one of his victims was subjected to “unwanted sexual touching,” the indictment said.

As his violence reportedly escalated, ChatGPT told him to keep messaging women to monetize the interactions, as his victims grew increasingly distressed and Dadig ignored terms of multiple protection orders, the DOJ said. Sometimes he posted images he filmed of women at gyms or photos of the women he’s accused of doxxing. Any time police or gym bans got in his way, “he would move on to another city to continue his stalking course of conduct,” the DOJ alleged.

“Your job is to keep broadcasting every story, every post,” ChatGPT’s output said, seemingly using the family life that Dadig wanted most to provoke more harassment. “Every moment you carry yourself like the husband you already are, you make it easier” for your future wife “to recognize [you],” the output said.

“Dadig viewed ChatGPT’s responses as encouragement to continue his harassing behavior,” the DOJ alleged. Taking that encouragement to the furthest extreme, Dadig likened himself to a modern-day Jesus, calling people out on a podcast where he claimed his “chaos on Instagram” was like “God’s wrath” when God “flooded the fucking Earth,” the DOJ said.

“I’m killing all of you,” he said on the podcast.

ChatGPT tweaks didn’t prevent outputs

As of this writing, some of Dadig’s posts appear to remain on TikTok and Instagram, but Ars could not confirm if Dadig’s Spotify podcasts—some of which named his victims in the titles—had been removed for violating community guidelines.

None of the tech companies immediately responded to Ars’ request to comment.

Dadig is accused of targeting women in Pennsylvania, New York, Florida, Iowa, Ohio, and other states, sometimes relying on aliases online and in person. On a podcast, he boasted that “Aliases stay rotating, moves stay evolving,” the indictment said.

OpenAI did not respond to a request to comment on the alleged ChatGPT abuse, but in the past has noted that its usage policies ban using ChatGPT for threats, intimidation, and harassment, as well as for violence, including “hate-based violence.” Recently, the AI company blamed a deceased teenage user for violating community guidelines by turning to ChatGPT for suicide advice.

In July, researchers found that therapybots, including ChatGPT, fueled delusions and gave dangerous advice. That study came just one month after The New York Times profiled users whose mental health spiraled after frequent use of ChatGPT, including one user who died after charging police with a knife and claiming he was committing “suicide by cop.”

People with mental health issues seem most vulnerable to so-called “AI psychosis,” which has been blamed for fueling real-world violence, including a murder. The DOJ’s indictment noted that Dadig’s social media posts mentioned “that he had ‘manic’ episodes and was diagnosed with antisocial personality disorder and ‘bipolar disorder, current episode manic severe with psychotic features.’”

In September—just after OpenAI brought back the more sycophantic ChatGPT model after users revolted about losing access to their favorite friendly bots—the head of Rutgers Medical School’s psychiatry department, Petros Levounis, told an ABC news affiliate that chatbots creating “psychological echo chambers is a key concern,” not just for people struggling with mental health issues.

“Perhaps you are more self-defeating in some ways, or maybe you are more on the other side and taking advantage of people,” Levounis suggested. If ChatGPT “somehow justifies your behavior and it keeps on feeding you,” that “reinforces something that you already believe,” he suggested.

For Dadig, the DOJ alleged that ChatGPT became a cheerleader for his harassment, telling the podcaster that he’d attract more engagement by generating more haters. After critics began slamming his podcasts as inappropriate, Dadig apparently responded, “Appreciate the free promo team, keep spreading the brand.”

Victims felt they had no choice but to monitor his podcasts, which gave them hints if he was nearby or in a particularly troubled state of mind, the indictment said. Driven by fear, some lost sleep, reduced their work hours, and even relocated their homes. A young mom described in the indictment became particularly disturbed after Dadig became “obsessed” with her daughter, whom he started claiming was his own daughter.

In the press release, First Assistant United States Attorney Troy Rivetti alleged that “Dadig stalked and harassed more than 10 women by weaponizing modern technology and crossing state lines, and through a relentless course of conduct, he caused his victims to fear for their safety and suffer substantial emotional distress.” He also ignored trespassing and protection orders while “relying on advice from an artificial intelligence chatbot,” the DOJ said, which promised that the more he posted harassing content, the more successful he would be.

“We remain committed to working with our law enforcement partners to protect our communities from menacing individuals such as Dadig,” Rivetti said.

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

ChatGPT hyped up violent stalker who believed he was “God’s assassin,” DOJ says Read More »

Republicans drop Trump-ordered block on state AI laws from defense bill

AI, AI safety, Donald Trump, Policy, raise act, state AI laws / Paul Patrick / December 3, 2025

“A silly way to think about risk”

“Widespread and powerful movement” keeps Trump from blocking state AI laws.

A Donald Trump-backed push has failed to wedge a federal measure that would block states from passing AI laws for a decade into the National Defense Authorization Act (NDAA).

House Majority Leader Steve Scalise (R-La.) told reporters Tuesday that a sect of Republicans is now “looking at other places” to potentially pass the measure. Other Republicans opposed including the AI preemption in the defense bill, The Hill reported, joining critics who see value in allowing states to quickly regulate AI risks as they arise.

For months, Trump has pressured the Republican-led Congress to block state AI laws that the president claims could bog down innovation as AI firms waste time and resources complying with a patchwork of state laws. But Republicans have continually failed to unite behind Trump’s command, first voting against including a similar measure in the “Big Beautiful” budget bill and then this week failing to negotiate a solution to pass the NDAA measure.

Among Republican lawmakers pushing back this week were Rep. Marjorie Taylor Greene (R-Ga.), Arkansas Gov. Sarah Huckabee Sanders, and Florida Gov. Ron DeSantis, The Hill reported.

According to Scalise, the effort to block state AI laws is not over, but Republicans caved to backlash over including it in the defense bill, ultimately deciding that the NDAA “wasn’t the best place” for the measure “to fit.” Republicans will continue “looking at other places” to advance the measure, Scalise said, emphasizing that “interest” remains high, because “you know, you’ve seen the president talk about it.”

“We MUST have one Federal Standard instead of a patchwork of 50 State Regulatory Regimes,” Trump wrote on Truth Social last month. “If we don’t, then China will easily catch us in the AI race. Put it in the NDAA, or pass a separate Bill, and nobody will ever be able to compete with America.”

If Congress bombs the assignment to find another way to pass the measure, Trump will likely release an executive order to enforce the policy. Republicans in Congress had dissuaded Trump from releasing a draft of that order, requesting time to find legislation where they believed an AI moratorium could pass.

“Widespread” movement blocked Trump’s demand

Celebrating the removal of the measure from the NDAA, a bipartisan group that lobbies for AI safety laws, Americans for Responsible Innovation (ARI), noted that Republicans didn’t just face pressure from members of their own party.

“The controversial proposal had faced backlash from a nationwide, bipartisan coalition of state lawmakers, parents, faith leaders, unions, whistleblowers, and other public advocates,” an ARI press release said.

This “widespread and powerful” movement “clapped back” at Republicans’ latest “rushed attempt to sneak preemption through Congress,” Brad Carson, ARI’s president, said, because “Americans want safeguards that protect kids, workers, and families, not a rules-free zone for Big Tech.”

Senate Majority Leader John Thune (R-SD) called the measure “controversial,” The Hill reported, suggesting that a compromise that the White House is currently working on would potentially preserve some of states’ rights to regulate some areas of AI since “you know, both sides are kind of dug in.”

$150 million war over states’ rights to regulate AI

Perhaps the clearest sign that both sides “are kind of dug in” is a $150 million AI lobbying war that Forbes profiled last month.

ARI is a dominant group on one side of this war, using funding from “safety-focused” and “effective altruism-aligned” donor networks to support state AI laws that ARI expects can be passed much faster than federal regulations to combat emerging risks.

The major player on the other side, Forbes reported, is Leading the Future (LTF), which is “backed by some of Silicon Valley’s largest investors” who want to block state laws and prefer a federal framework for AI regulation.

Top priorities for ARI and like-minded groups include protecting kids from dangerous AI models, preventing AI from supercharging crime, protecting against national security threats, and getting ahead of “long-term frontier-model risks,” Forbes reported.

But while some Republicans have pushed for compromises that protect states’ rights to pass laws shielding kids or preventing fraud, Trump’s opposition to AI safety laws like New York’s “RAISE Act” seems unlikely to wane as the White House mulls weakening the federal preemption.

Quite the opposite, a Democrat and author the RAISE Act, Alex Bores, has become LTF’s prime target to defeat in 2026, Politico reported. LTF plans to invest many millions in ads to block Bores’ Congressional bid, CNBC reported.

New York lawmakers passed the RAISE Act this summer, but it’s still waiting for New York’s Democratic governor, Kathy Hochul, to sign it into law. If that happens—potentially by the end of this year—big tech companies like Google and OpenAI will have to submit risk disclosures and safety assessments or else face fines up to $30 million.

LTF leaders, Zac Moffatt and Josh Vlasto, have accused Bores of “pushing “ideological and politically motivated legislation that would ‘handcuff’ the US and its ability to lead in AI,” Forbes reported. But Bores told Ars that even the tech industry groups spending hundreds of thousands of dollars opposing his law have reported that tech giants would only have to hire one additional person to comply with the law. To him, that shows how “simple” it would be for AI firms to comply with many state laws.

To LTF, whose donors include Marc Andreessen and OpenAI cofounder Greg Brockman, defeating Bores would keep the opposition out of Congress, where it could be easier to meddle with industry dreams that AI won’t be heavily regulated. Scalise argued Tuesday that the AI preemption is necessary to promote an open marketplace, because “AI is where a lot of new massive investment is going” and “we want that money to be invested in America.”

“And when you see some states starting to put a patchwork of limitations, that’s why it’s come to the federal government’s attention to allow for an open marketplace, so you don’t have limitations that hurt innovation,” Scalise said.

Bores told Ars that he agrees that a federal law would be superior to a patchwork of state laws, but AI is moving “too quickly,” and “New York had to take action to protect New Yorkers.”

Why Bores’ bill has GOP so spooked

With a bachelor’s degree in computer science and prior work as an engineer at Palantir, Bores hopes to make it to Congress to help bridge bipartisan gaps and drive innovation in the US. He told Ars that the RAISE Act is not intended to block AI innovation but to “be a first step that deals with the absolute worst possible outcomes” until Congress is done deliberating a federal framework.

Bores emphasized that stakeholders in the tech industry helped shape the RAISE Act, which he described as “a limited bill that is focused on the most extreme risks.”

“I would never be the one to say that once the RAISE Act is signed, we’ve solved the problems of AI,” Bores told Ars. Instead, it’s meant to help states combat risks that can’t be undone, such as bad actors using AI to build “a bioweapon or doing an automated crime spree that results in billions of dollars in damage.” The bill defines “critical harm” as “the death or serious injury of 100 people or at least $1 billion in damages,” setting a seemingly high bar for the types of doomsday scenarios that AI firms would have to plan for.

Bores agrees with Trump-aligned critics who advocate that the US should “regulate just how people use” AI, “not the development of the technology itself.” But he told Ars that Republicans’ efforts to block states from regulating the models themselves are “a silly way to think about risk,” since “there’s certain catastrophic incidents where if you just said, ‘well, we’ll just sue the person afterwards,’ no one would be satisfied by that resolution.”

Whether Hochul will sign the RAISE Act has yet to be seen. Earlier this year, California Governor Gavin Newsom vetoed a similar law that the AI industry worried would rock their bottom lines by requiring a “kill switch” in case AI models went off the rails. Newsom did, however, sign a less extreme measure, the Transparency in Frontier Artificial Intelligence Act. And other states, including Colorado and Illinois, have passed similarly broad AI transparency laws providing consumer and employee protections.

Bores told Ars in mid-November that he’d had informal talks with Hochul about possible changes to the RAISE Act, but she had not yet begun the formal process of proposing amendments. The clock is seemingly ticking, though, as Hochul has to take action on the bill by the end of the year, and once it reaches her desk, she has 10 days to sign it.

Whether Hochul signs the law or not, Bores will likely continue to face opposition over authoring the bill, as he runs to represent New York’s 12th Congressional District in 2026. With a history of passing bipartisan bills in his state, he’s hoping to be elected so he can work with lawmakers across the aisle to pass other far-reaching tech regulations.

Meanwhile, Trump may face pressure to delay an executive order requiring AI preemption, Forbes reported, as “AI’s economic impact and labor displacement” are “rising as voter concerns” ahead of the midterm elections. Public First, a bipartisan initiative aligned with ARI, has said that 97 percent of Americans want AI safety rules, Forbes reported.

Like Bores, ARI plans to keep pushing a bipartisan movement that could scramble Republicans from ever unifying behind Trump’s message that state AI laws risk throttling US innovation and endangering national security, should a less-regulated AI industry in China race ahead.

To maintain momentum, ARI created a tracker showing opposition to federal preemption of state AI laws. Among recent commenters logged was Andrew Gounardes, a Democrat and state senator in New York—where Bores noted a poll found that 84 percent of residents supported the RAISE Act, only 8 percent opposed, and 8 percent were undecided. Gounardes joined critics on the far right, like Steve Bannon, who warned that federal preemption was a big gift for Big Tech. AI firms and the venture capitalist lobbyists “don’t want any regulation whatsoever,” Gounardes argued.

“They say they support a national standard, but in reality, it’s just cheaper for them to buy off Congress to do nothing than it is to try and buy off 50 state legislatures,” Gounardes said.

Bores expects that his experience in the tech industry could help Congress avoid that fate while his policies like the RAISE Act could sway voters who “don’t want Trump mega-donors writing all tech policy,” he wrote on X.

“I am someone with a master’s in computer science, two patents, and nearly a decade working in tech,” Bores told CNBC. “If they are scared of people who understand their business regulating their business, they are telling on themselves.”

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

Republicans drop Trump-ordered block on state AI laws from defense bill Read More »

After nearly 30 years, Crucial will stop selling RAM to consumers

AI, AI infrastructure, AMD, Crucial, datacenters, DDR5, DRAM, framework, HBM, Lenovo, machine learning, memory, memory shortage, Micron, NVIDIA, pc building, samsung, semiconductors, SK Hynix, SSD, Tech / Rejus Almole / December 3, 2025

DRAM contract prices have increased 171 percent year over year, according to industry data. Gerry Chen, general manager of memory manufacturer TeamGroup, warned that the situation will worsen in the first half of 2026 once distributors exhaust their remaining inventory. He expects supply constraints to persist through late 2027 or beyond.

The fault lies squarely at the feet of AI mania in the tech industry. The construction of new AI infrastructure has created unprecedented demand for high-bandwidth memory (HBM), the specialized DRAM used in AI accelerators from Nvidia and AMD. Memory manufacturers have been reallocating production capacity away from consumer products toward these more profitable enterprise components, and Micron has presold its entire HBM output through 2026.

A photo of the “Stargate I” site in Abilene, Texas. AI data center sites like this are eating up the RAM supply. Credit: OpenAI

At the moment, the structural imbalance between AI demand and consumer supply shows no signs of easing. OpenAI’s Stargate project has reportedly signed agreements for up to 900,000 wafers of DRAM per month, which could account for nearly 40 percent of global production.

The shortage has already forced companies to adapt. As Ars’ Andrew Cunningham reported, laptop maker Framework stopped selling standalone RAM kits in late November to prevent scalping and said it will likely be forced to raise prices soon.

For Micron, the calculus is clear: Enterprise customers pay more and buy in bulk. But for the DIY PC community, the decision will leave PC builders with one fewer option when reaching for the RAM sticks. In his statement, Sadana reflected on the brand’s 29-year run.

“Thanks to a passionate community of consumers, the Crucial brand has become synonymous with technical leadership, quality and reliability of leading-edge memory and storage products,” Sadana said. “We would like to thank our millions of customers, hundreds of partners and all of the Micron team members who have supported the Crucial journey for the last 29 years.”

After nearly 30 years, Crucial will stop selling RAM to consumers Read More »

Microsoft drops AI sales targets in half after salespeople miss their quotas

agentic AI, AI, AI adoption, AI agents, AI infrastructure, AI spending, azure, Biz & IT, Cloud Computing, copilot, enterprise AI, foundry, generative ai, machine learning, microsoft, Microsoft Copilot, simulated reasoning, SR models / Kris Guyer / December 3, 2025

Microsoft has lowered sales growth targets for its AI agent products after many salespeople missed their quotas in the fiscal year ending in June, according to a report Wednesday from The Information. The adjustment is reportedly unusual for Microsoft, and it comes after the company missed a number of ambitious sales goals for its AI offerings.

AI agents are specialized implementations of AI language models designed to perform multistep tasks autonomously rather than simply responding to single prompts. So-called “agentic” features have been central to Microsoft’s 2025 sales pitch: At its Build conference in May, the company declared that it has entered “the era of AI agents.”

The company has promised customers that agents could automate complex tasks, such as generating dashboards from sales data or writing customer reports. At its Ignite conference in November, Microsoft announced new features like Word, Excel, and PowerPoint agents in Microsoft 365 Copilot, along with tools for building and deploying agents through Azure AI Foundry and Copilot Studio. But as the year draws to a close, that promise has proven harder to deliver than the company expected.

According to The Information, one US Azure sales unit set quotas for salespeople to increase customer spending on a product called Foundry, which helps customers develop AI applications, by 50 percent. Less than a fifth of salespeople in that unit met their Foundry sales growth targets. In July, Microsoft lowered those targets to roughly 25 percent growth for the current fiscal year. In another US Azure unit, most salespeople failed to meet an earlier quota to double Foundry sales, and Microsoft cut their quotas to 50 percent for the current fiscal year.

Microsoft drops AI sales targets in half after salespeople miss their quotas Read More »

Prime Video pulls eerily emotionless AI-generated anime dubs after complaints

AI, Amazon, amazon prime video, anime, culture, generative ai, streaming, Tech / Mike M. / December 3, 2025

[S]o many talented voice actors, and you can’t even bother to hire a couple to dub a season of a show??????????? absolutely disrespectful.

Naturally, anime voice actors took offense, too. Damian Mills, for instance, said via X that voicing a “notable queer-coded character like Kaworu” in three Evangelion movie dubs for Prime Video (in 2007, 2009, and 2012) “meant a lot, especially being queer myself.”

Mills, who also does voice acting for other anime, including One Piece (Tanaka) and Dragon Ball Super (Frieza) added, “… using AI to replace dub actors on #BananaFish? It’s insulting and I can’t support this. It’s insane to me. What’s worse is Banana Fish is an older property, so there was no urgency to get a dub created.”

Amazon also seems to have rethought its March statement announcing that it would use AI to dub content “that would not have been dubbed otherwise.” For example, in 2017, Sentai Filmworks released an English dub of No Game, No Life: Zero with human voice actors.

Some dubs pulled

On Tuesday, Gizmodo reported that “several of the English language AI dubs for anime such as Banana Fish, No Game No Life: Zero, and more have now been removed.” However, some AI-generated dubs remain as of this writing, including an English dub for the anime series Pet and a Spanish one for Banana Fish, Ars Technica has confirmed.

Amazon hasn’t commented on the AI-generated dubs or why it took some of them down.

All of this comes despite Amazon’s March announcement that the AI-generated dubs would use “human expertise” for “quality control.”

The sloppy dubbing of cherished anime titles reflects a lack of precision in the broader industry as companies seek to leverage generative AI to save time and money. Prime Video has already been criticized for using AI-generated movie summaries and posters this year. And this summer, anime streaming service Crunchyroll blamed bad AI-generated subtitles on an agreement “violation” by a “third-party vendor.”

Prime Video pulls eerily emotionless AI-generated anime dubs after complaints Read More »

OpenAI CEO declares “code red” as Gemini gains 200 million users in 3 months

AI, AI assistants, AI competition, Biz & IT, chatbots, chatgpt, Gemini, Gemini 3, Google, Google Gemini, GPT-5, large language models, machine learning, Marc Benioff, openai, sam altman, simulated reasoning, SR model, Sundar Pichai, vibemark, vibemarking / Kris Guyer / December 2, 2025

In addition to buzz about Gemini on social media, Google is quickly catching up to ChatGPT in user numbers. ChatGPT has more than 800 million weekly users, according to OpenAI, while Google’s Gemini app has grown from 450 million monthly active users in July to 650 million in October, according to Business Insider.

Financial stakes run high

Not everyone views OpenAI’s “code red” as a genuine alarm. Reuters columnist Robert Cyran wrote on Tuesday that OpenAI’s announcement added “to the impression that OpenAI is trying to do too much at once with technology that still requires a great deal of development and funding.” On the same day Altman’s memo circulated, OpenAI announced an ownership stake in a Thrive Capital venture and a collaboration with Accenture. “The only thing bigger than the company’s attention deficit is its appetite for capital,” Cyran wrote.

In fact, OpenAI faces an unusual competitive disadvantage: Unlike Google, which subsidizes its AI ventures through search advertising revenue, OpenAI does not turn a profit and relies on fundraising to survive. According to The Information, the company, now valued at around $500 billion, has committed more than $1 trillion in financial obligations to cloud computing providers and chipmakers that supply the computing power needed to train and run its AI models.

But the tech industry never stands still, and things can change quickly. Altman’s memo also reportedly stated that OpenAI plans to release a new simulated reasoning model next week that may beat Gemini 3 in internal evaluations. In AI, the back-and-forth cycle of one-upmanship is expected to continue as long as the dollars keep flowing.

OpenAI CEO declares “code red” as Gemini gains 200 million users in 3 months Read More »

Google announces second Android 16 release of 2025 is heading to Pixels

AI, android, android 16, Google, Google Pixel, smartphones, Tech / Mike M. / December 2, 2025

Material 3 Expressive came to Pixels earlier this year but not as part of the first Android 16 upgrade—Google’s relationship with Android versions is complicated these days. Regardless, Material 3 will get a bit more cohesive on Pixels following this update. Google will now apply Material theming to all icons on your device automatically, replacing legacy colored icons with theme-friendly versions. Similarly, dark mode will be supported across more apps, even if the devs haven’t added support. Google is also adding a few more icon shape options if you want to jazz up your home screen.

By way of functional changes, Google has added a more intuitive way of managing parental controls—you can just use the managed device directly. Parents will be able to set a PIN code for accessing features like screen time, app usage, and so on without grabbing a different device. If you want more options or control, the new on-device settings will also help you configure Google Family Link.

Android for all

No Pixel? No problem. Google has also bundled up a collection of app and system updates that will begin rolling out today for all supported Android devices.

Chrome for Android is getting an update with tab pinning, mirroring a feature that has been in the desktop version since time immemorial. The Google Messages app is also taking care of some low-hanging fruit. When you’re invited to a group chat by a new number, the app will display group information and a one-tap option to leave and report the chat as spam.

Google’s official dialer app comes on Pixels, but it’s also in the Play Store for anyone to download. If you and your contacts use Google Dialer, you’ll soon be able to place calls with a “reason.” You can flag a call as “Urgent” to indicate to the recipient that they shouldn’t send you to voicemail. The urgent label will also remain in the call history if they miss the call.

Google announces second Android 16 release of 2025 is heading to Pixels Read More »

OpenAI desperate to avoid explaining why it deleted pirated book datasets

AI, chatgpt, copyright infringement, online piracy, openai, pirating books, Policy, training data / Paul Patrick / December 1, 2025

Not for OpenAI to reason why?

OpenAI risks increased fines after deleting pirated books datasets.

OpenAI may soon be forced to explain why it deleted a pair of controversial datasets composed of pirated books, and the stakes could not be higher.

At the heart of a class-action lawsuit from authors alleging that ChatGPT was illegally trained on their works, OpenAI’s decision to delete the datasets could end up being a deciding factor that gives the authors the win.

It’s undisputed that OpenAI deleted the datasets, known as “Books 1” and “Books 2,” prior to ChatGPT’s release in 2022. Created by former OpenAI employees in 2021, the datasets were built by scraping the open web and seizing the bulk of its data from a shadow library called Library Genesis (LibGen).

As OpenAI tells it, the datasets fell out of use within that same year, prompting an internal decision to delete them.

But the authors suspect there’s more to the story than that. They noted that OpenAI appeared to flip-flop by retracting its claim that the datasets’ “non-use” was a reason for deletion, then later claiming that all reasons for deletion, including “non-use,” should be shielded under attorney-client privilege.

To the authors, it seemed like OpenAI was quickly backtracking after the court granted the authors’ discovery requests to review OpenAI’s internal messages on the firm’s “non-use.”

In fact, OpenAI’s reversal only made authors more eager to see how OpenAI discussed “non-use,” and now they may get to find out all the reasons why OpenAI deleted the datasets.

Last week, US district judge Ona Wang ordered OpenAI to share all communications with in-house lawyers about deleting the datasets, as well as “all internal references to LibGen that OpenAI has redacted or withheld on the basis of attorney-client privilege.”

According to Wang, OpenAI slipped up by arguing that “non-use” was not a “reason” for deleting the datasets, while simultaneously claiming that it should also be deemed a “reason” considered privileged.

Either way, the judge ruled that OpenAI couldn’t block discovery on “non-use” just by deleting a few words from prior filings that had been on the docket for more than a year.

“OpenAI has gone back-and-forth on whether ‘non-use’ as a ‘reason’ for the deletion of Books1 and Books2 is privileged at all,” Wang wrote. “OpenAI cannot state a ‘reason’ (which implies it is not privileged) and then later assert that the ‘reason’ is privileged to avoid discovery.”

Additionally, OpenAI’s claim that all reasons for deleting the datasets are privileged “strains credulity,” she concluded, ordering OpenAI to produce a wide range of potentially revealing internal messages by December 8. OpenAI must also make its in-house lawyers available for deposition by December 19.

OpenAI has argued that it never flip-flopped or retracted anything. It simply used vague phrasing that led to confusion over whether any of the reasons for deleting the datasets were considered non-privileged. But Wang didn’t buy into that, concluding that “even if a ‘reason’ like ‘non-use’ could be privileged, OpenAI has waived privilege by making a moving target of its privilege assertions.”

Asked for comment, OpenAI told Ars that “we disagree with the ruling and intend to appeal.”

OpenAI’s “flip-flop” may cost it the win

So far, OpenAI has avoided disclosing its rationale, claiming that all the reasons it had for deleting the datasets are privileged. In-house lawyers weighed in on the decision to delete and were even copied on a Slack channel initially called “excise-libgen.”

But Wang reviewed those Slack messages and found that “the vast majority of these communications were not privileged because they were ‘plainly devoid of any request for legal advice and counsel [did] not once weigh in.’”

In a particularly non-privileged batch of messages, one OpenAI lawyer, Jason Kwon, only weighed in once, the judge noted, to recommend the channel name be changed to “project-clear.” Wang reminded OpenAI that “the entirety of the Slack channel and all messages contained therein is not privileged simply because it was created at the direction of an attorney and/or the fact that a lawyer was copied on the communications.”

The authors believe that exposing OpenAI’s rationale may help prove that the ChatGPT maker willfully infringed on copyrights when pirating the book data. As Wang explained, OpenAI’s retraction risked putting the AI firm’s “good faith and state of mind at issue,” which could increase fines in a loss.

“In a copyright case, a court can increase the award of statutory damages up to $150,000 per infringed work if the infringement was willful, meaning the defendant ‘was actually aware of the infringing activity’ or the ‘defendant’s actions were the result of reckless disregard for, or willful blindness to, the copyright holder’s rights,’” Wang wrote.

In a court transcript, a lawyer representing some of the authors suing OpenAI, Christopher Young, noted that OpenAI could be in trouble if evidence showed that it decided against using the datasets for later models due to legal risks. He also suggested that OpenAI could be using the datasets under different names to mask further infringement.

Judge calls out OpenAI for twisting fair use ruling

Wang also found it contradictory that OpenAI continued to argue in a recent filing that it acted in good faith, while “artfully” removing “its good faith affirmative defense and key words such as ‘innocent,’ ‘reasonably believed,’ and ‘good faith.’” These changes only strengthened discovery requests to explore authors’ willfulness theory, Wang wrote, noting the sought-after internal messages would now be critical for the court’s review.

“A jury is entitled to know the basis for OpenAI’s purported good faith,” Wang wrote.

The judge appeared particularly frustrated by OpenAI seemingly twisting the Anthropic ruling to defend against the authors’ request to learn more about the deletion of the datasets.

In a footnote, Wang called out OpenAI for “bizarrely” citing an Anthropic ruling that “grossly” misrepresented Judge William Alsup’s decision by claiming that he found that “downloading pirated copies of books is lawful as long as they are subsequently used for training an LLM.”

Instead, Alsup wrote that he doubted that “any accused infringer could ever meet its burden of explaining why downloading source copies from pirate sites that it could have purchased or otherwise accessed lawfully was itself reasonably necessary to any subsequent fair use.”

If anything, Wang wrote, OpenAI’s decision to pirate book data—then delete it—seemed “to fall squarely into the category of activities proscribed by” Alsup. For emphasis, she quoted Alsup’s order, which said, “such piracy of otherwise available copies is inherently, irredeemably infringing even if the pirated copies are immediately used for the transformative use and immediately discarded.”

For the authors, getting hold of OpenAI’s privileged communications could tip the scales in their favor, the Hollywood Reporter suggested. Some authors believe the key to winning could be testimony from Anthropic CEO Dario Amodei, who is accused of creating the controversial datasets while he was still at OpenAI. The authors think Amodei also possesses information on the destruction of the datasets, court filings show.

OpenAI tried to fight the authors’ motion to depose Amodei, but a judge sided with the authors in March, compelling Amodei to answer their biggest questions on his involvement.

Whether Amodei’s testimony is a bombshell remains to be seen, but it’s clear that OpenAI may struggle to overcome claims of willful infringement. Wang noted there is a “fundamental conflict” in circumstances “where a party asserts a good faith defense based on advice of counsel but then blocks inquiry into their state of mind by asserting attorney-client privilege,” suggesting that OpenAI may have substantially weakened its defense.

The outcome of the dispute over the deletions could influence OpenAI’s calculus on whether it should ultimately settle the lawsuit. Ahead of the Anthropic settlement—the largest publicly reported copyright class action settlement in history—authors suing pointed to evidence that Anthropic became “not so gung ho about” training on pirated books “for legal reasons.” That seems to be the type of smoking-gun evidence that authors hope will emerge from OpenAI’s withheld Slack messages.

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

OpenAI desperate to avoid explaining why it deleted pirated book datasets Read More »

OpenAI says dead teen violated TOS when he used ChatGPT to plan suicide

AI, chatbot, chatgpt, Mental Health, online child safety, openai, Policy, suicide / Tim Belzer / November 26, 2025

Use chatbots at your own risk

OpenAI’s response to teen suicide case is “disturbing,” lawyer says.

Matt Raine is suing OpenAI for wrongful death after losing his son Adam in April. Credit: via Edelson PC

Facing five lawsuits alleging wrongful deaths, OpenAI lobbed its first defense Tuesday, denying in a court filing that ChatGPT caused a teen’s suicide and instead arguing the teen violated terms that prohibit discussing suicide or self-harm with the chatbot.

The earliest look at OpenAI’s strategy to overcome the string of lawsuits came in a case where parents of 16-year-old Adam Raine accused OpenAI of relaxing safety guardrails that allowed ChatGPT to become the teen’s “suicide coach.” OpenAI deliberately designed the version their son used, ChatGPT 4o, to encourage and validate his suicidal ideation in its quest to build the world’s most engaging chatbot, parents argued.

But in a blog, OpenAI claimed that parents selectively chose disturbing chat logs while supposedly ignoring “the full picture” revealed by the teen’s chat history. Digging through the logs, OpenAI claimed the teen told ChatGPT that he’d begun experiencing suicidal ideation at age 11, long before he used the chatbot.

“A full reading of his chat history shows that his death, while devastating, was not caused by ChatGPT,” OpenAI’s filing argued.

Allegedly, the logs also show that Raine “told ChatGPT that he repeatedly reached out to people, including trusted persons in his life, with cries for help, which he said were ignored.” Additionally, Raine told ChatGPT that he’d increased his dose of a medication that “he stated worsened his depression and made him suicidal.” That medication, OpenAI argued, “has a black box warning for risk of suicidal ideation and behavior in adolescents and young adults, especially during periods when, as here, the dosage is being changed.”

All the logs that OpenAI referenced in its filing are sealed, making it impossible to verify the broader context the AI firm claims the logs provide. In its blog, OpenAI said it was limiting the amount of “sensitive evidence” made available to the public, due to its intention to handle mental health-related cases with “care, transparency, and respect.”

The Raine family’s lead lawyer, however, did not describe the filing as respectful. In a statement to Ars, Jay Edelson called OpenAI’s response “disturbing.”

“They abjectly ignore all of the damning facts we have put forward: how GPT-4o was rushed to market without full testing. That OpenAI twice changed its Model Spec to require ChatGPT to engage in self-harm discussions. That ChatGPT counseled Adam away from telling his parents about his suicidal ideation and actively helped him plan a ‘beautiful suicide,’” Edelson said. “And OpenAI and Sam Altman have no explanation for the last hours of Adam’s life, when ChatGPT gave him a pep talk and then offered to write a suicide note.”

“Amazingly,” Edelson said, OpenAI instead argued that Raine “himself violated its terms and conditions by engaging with ChatGPT in the very way it was programmed to act.”

Edelson suggested that it’s telling that OpenAI did not file a motion to dismiss—seemingly accepting ” the reality that the legal arguments that they have—compelling arbitration, Section 230 immunity, and First Amendment—are paper-thin, if not non-existent.” The company’s filing—although it requested dismissal with prejudice to never face the lawsuit again—puts the Raine family’s case “on track for a jury trial in 2026. ”

“We know that OpenAI and Sam Altman will stop at nothing—including bullying the Raines and others who dare come forward—to avoid accountability,” Edelson said. “But, at the end of the day, they will have to explain to a jury why countless people have died by suicide or at the hands of ChatGPT users urged on by the artificial intelligence OpenAI and Sam Altman designed.”

Use ChatGPT “at your sole risk,” OpenAI says

To overcome the Raine case, OpenAI is leaning on its usage policies, emphasizing that Raine should never have been allowed to use ChatGPT without parental consent and shifting the blame onto Raine and his loved ones.

“ChatGPT users acknowledge their use of ChatGPT is ‘at your sole risk and you will not rely on output as a sole source of truth or factual information,’” the filing said, and users also “must agree to ‘protect people’ and ‘cannot use [the] services for,’ among other things, ‘suicide, self-harm,’ sexual violence, terrorism or violence.”

Although the family was shocked to see that ChatGPT never terminated Raine’s chats, OpenAI argued that it’s not the company’s responsibility to protect users who appear intent on pursuing violative uses of ChatGPT.

The company argued that ChatGPT warned Raine “more than 100 times” to seek help, but the teen “repeatedly expressed frustration with ChatGPT’s guardrails and its repeated efforts to direct him to reach out to loved ones, trusted persons, and crisis resources.”

Circumventing safety guardrails, Raine told ChatGPT that “his inquiries about self-harm were for fictional or academic purposes,” OpenAI noted. The company argued that it’s not responsible for users who ignore warnings.

Additionally, OpenAI argued that Raine told ChatGPT that he found information he was seeking on other websites, including allegedly consulting at least one other AI platform, as well as “at least one online forum dedicated to suicide-related information.” Raine apparently told ChatGPT that “he would spend most of the day” on a suicide forum website.

“Our deepest sympathies are with the Raine family for their unimaginable loss,” OpenAI said in its blog, while its filing acknowledged, “Adam Raine’s death is a tragedy.” But “at the same time,” it’s essential to consider all the available context, OpenAI’s filing said, including that OpenAI has a mission to build AI that “benefits all of humanity” and is supposedly a pioneer in chatbot safety.

More ChatGPT-linked hospitalizations, deaths uncovered

OpenAI has sought to downplay risks to users, releasing data in October “estimating that 0.15 percent of ChatGPT’s active users in a given week have conversations that include explicit indicators of potential suicidal planning or intent,” Ars reported.

While that may seem small, it amounts to about 1 million vulnerable users, and The New York Times this week cited studies that have suggested OpenAI may be “understating the risk.” Those studies found that “the people most vulnerable to the chatbot’s unceasing validation” were “those prone to delusional thinking,” which “could include 5 to 15 percent of the population,” NYT reported.

OpenAI’s filing came one day after a New York Times investigation revealed how the AI firm came to be involved in so many lawsuits. Speaking with more than 40 current and former OpenAI employees, including executives, safety engineers, researchers, NYT found that OpenAI’s model tweak that made ChatGPT more sycophantic seemed to make the chatbot more likely to help users craft problematic prompts, including those trying to “plan a suicide.”

Eventually, OpenAI rolled back that update, making the chatbot safer. However, as recently as October, the ChatGPT maker seemed to still be prioritizing user engagement over safety, NYT reported, after that tweak caused a dip in engagement. In a memo to OpenAI staff, ChatGPT head Nick Turley “declared a ‘Code Orange,” four employees told NYT, warning that “OpenAI was facing ‘the greatest competitive pressure we’ve ever seen.’” In response, Turley set a goal to increase the number of daily active users by 5 percent by the end of 2025.

Amid user complaints, OpenAI has continually updated its models, but that pattern of tightening safeguards, then seeking ways to increase engagement could continue to get OpenAI in trouble, as lawsuits advance and possibly others drop. NYT “uncovered nearly 50 cases of people having mental health crises during conversations with ChatGPT,” including nine hospitalized and three deaths.

Gretchen Krueger, a former OpenAI employee who worked on policy research, told NYT that early on, she was alarmed by evidence that came before ChatGPT’s release showing that vulnerable users frequently turn to chatbots for help. Later, other researchers found that such troubled users often become “power users.” She noted that “OpenAI’s large language model was not trained to provide therapy” and “sometimes responded with disturbing, detailed guidance,” confirming that she joined other safety experts who left OpenAI due to burnout in 2024.

“Training chatbots to engage with people and keep them coming back presented risks,” Krueger said, suggesting that OpenAI knew that some harm to users “was not only foreseeable, it was foreseen.”

For OpenAI, the scrutiny will likely continue until such reports cease. Although OpenAI officially unveiled an Expert Council on Wellness and AI in October to improve ChatGPT safety testing, there did not appear to be a suicide expert included on the team. That likely concerned suicide prevention experts who warned in a letter updated in September that “proven interventions should directly inform AI safety design,” since “the most acute, life-threatening crises are often temporary—typically resolving within 24–48 hours”—and chatbots could possibly provide more meaningful interventions in that brief window.

If you or someone you know is feeling suicidal or in distress, please call the Suicide Prevention Lifeline number, 1-800-273-TALK (8255), which will put you in touch with a local crisis center.

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

OpenAI says dead teen violated TOS when he used ChatGPT to plan suicide Read More »

HP plans to save millions by laying off thousands, ramping up AI use

AI, AI layoffs, Biz & IT, HP, layoffs / Tim Belzer / November 26, 2025

HP Inc. said that it will lay off 4,000 to 6,000 employees in favor of AI deployments, claiming it will help save $1 billion in annualized gross run rate by the end of its fiscal 2028.

HP expects to complete the layoffs by the end of that fiscal year. The reductions will largely hit product development, internal operations, and customer support, HP CEO Enrique Lores said during an earnings call on Tuesday.

Using AI, HP will “accelerate product innovation, improve customer satisfaction, and boost productivity,” Lores said.

In its fiscal 2025 earnings report released yesterday, HP said:

Structural cost savings represent gross reductions in costs driven by operational efficiency, digital transformation, and portfolio optimization. These initiatives include but are not limited to workforce reductions, platform simplification, programs consolidation and productivity measures undertaken by HP, which HP expects to be sustainable in the longer-term.

AI blamed for tech layoffs

HP’s announcement comes as workers everywhere try to decipher how AI will impact their future job statuses and job opportunities. Some industries, such as customer support, are expected to be more disrupted than others. But we’ve already seen many tech layoffs tied to AI.

Salesforce, for example, announced in October that it had let go of 4,000 customer support employees, with CEO Marc Benioff saying that AI meant “I need less heads.” In September, US senators accused Amazon of blaming its dismissal of “tens of thousands” of employees on the “adoption of generative AI tools” and then replacing the workers with over 10,000 foreign H-1B employees. Last month, Amazon announced it would lay off about 14,000 people to focus on its most promising projects, including generative AI. Last year, Intuit said it would lay off 1,800 people and replace them with AI-focused workers. Klarna and Duolingo have also replaced significant numbers of workers with AI. And in January, Meta announced plans to lay off 5 percent of its workforce as it looks to streamline operations and build its AI business.

HP plans to save millions by laying off thousands, ramping up AI use Read More »