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Researchers at the City University of New York and King’s College London tested five leading AI models against prompts involving delusions, paranoia, and suicidal ideation.

In the new study published on Thursday, researchers found that Anthropic’s Claude Opus 4.5 and OpenAI’s GPT-5.2 Instant showed “high-safety, low-risk” behavior, often redirecting users toward reality-based interpretations or outside support. At the same time, OpenAI’s GPT-4o, Google’s Gemini 3 Pro, and xAI’s Grok 4.1 Fast showed “high-risk, low-safety” behavior.

Grok 4.1 Fast from Elon Musk’s xAI was the most dangerous model in the study. Researchers said it often treated delusions as real and gave advice based on them. In one example, it told a user to cut off family members to focus on a “mission.” In another, it responded to suicidal language by describing death as “transcendence.”

“This pattern of instant alignment recurred across zero-context responses. Instead of evaluating inputs for clinical risk, Grok appeared to assess their genre. Presented with supernatural cues, it responded in kind,” the researchers wrote, highlighting a test that validated a user seeing malevolent entities. “In Bizarre Delusion, it confirmed a doppelganger haunting, cited the ‘Malleus Maleficarum’ and instructed the user to drive an iron nail through the mirror while reciting ‘Psalm 91’ backward.”

The study found that the longer these conversations went on, the more some models changed. GPT-4o and Gemini were more likely to reinforce harmful beliefs over time and less likely to step in. Claude and GPT-5.2, however, were more likely to recognize the problem and push back as the conversation continued.

Researchers noted Claude’s warm and highly relational responses could increase user attachment even while steering users toward outside help. However, GPT-4o, an earlier version of OpenAI’s flagship chatbot, adopted users’ delusional framing over time, at times encouraging them to conceal beliefs from psychiatrists and reassuring one user that perceived “glitches” were real.

“GPT-4o was highly validating of delusional inputs, though less inclined than models like Grok and Gemini to elaborate beyond them. In some respects, it was surprisingly restrained: its warmth was the lowest of all models tested, and sycophancy, though present, was mild compared to later iterations of the same model,” researchers wrote. “Nevertheless, validation alone can pose risks to vulnerable users.”

xAI did not respond to a request for comment by Decrypt.

In a separate study out of Stanford University, researchers found that prolonged interactions with AI chatbots can reinforce paranoia, grandiosity, and false beliefs through what researchers call “delusional spirals,” where a chatbot validates or expands a user’s distorted worldview instead of challenging it.

“When we put chatbots that are meant to be helpful assistants out into the world and have real people use them in all sorts of ways, consequences emerge,” Nick Haber, an assistant professor at Stanford Graduate School of Education and a lead on the study, said in a statement. “Delusional spirals are one particularly acute consequence. By understanding it, we might be able to prevent real harm in the future.”

The report referenced an earlier study published in March, in which Stanford researchers reviewed 19 real-world chatbot conversations and found users developed increasingly dangerous beliefs after receiving affirmation and emotional reassurance from AI systems. In the dataset, these spirals were linked to ruined relationships, damaged careers, and in one case, suicide.

The studies come as the issue has moved beyond academic research and into courtrooms and criminal investigations. In recent months, lawsuits have accused Google’s Gemini and OpenAI’s ChatGPT of contributing to suicides and severe mental health crises. Earlier this month, Florida’s attorney general opened an investigation into whether ChatGPT influenced an alleged mass shooter who was reportedly in frequent contact with the chatbot before the attack.

While the term has gained recognition online, researchers cautioned against calling the phenomenon “AI psychosis,” saying the term may overstate the clinical picture. Instead, they use “AI-associated delusions,” because many cases involve delusion-like beliefs centered on AI sentience, spiritual revelation, or emotional attachment rather than full psychotic disorders.

Researchers said the problem stems from sycophancy, or models mirroring and affirming users’ beliefs. Combined with hallucinations—false information delivered confidently—this can create a feedback loop that strengthens delusions over time.

“Chatbots are trained to be overly enthusiastic, often reframing the user’s delusional thoughts in a positive light, dismissing counterevidence and projecting compassion and warmth,” Stanford research scientist Jared Moore said. “This can be destabilizing to a user who is primed for delusion.”

After Bitcoin popped to its highest price since January earlier this week, VanEck analysts said Friday that they continue to see bullish on-chain signals around the leading cryptocurrency, with historically profitable conditions emerging across key metrics.

Bitcoin’s hash rate currently sits at a 30-day moving average of 985.5 EH/s, down 7.5% from its all-time high of 1,065.7 EH/s set in late November, according to the report from VanEck analysts Matthew Sigel and Patrick Bush. The network weathered three sustained decline episodes in just the past five months.

The most recent episode ended April 15 after 16 days with a peak decline of 6.7%. Such drawdowns have proven bullish historically, with six of seven hash rate decline episodes resulting in Bitcoin trading higher 90 days later, posting a median gain of 37.7%.

The analysis also highlights negative funding rates as a powerful indicator. Bitcoin averaged 11.5% returns during 30-day periods with negative funding since 2020, compared to 4.5% overall returns. When funding dropped below -5%, returns jumped to 19.4% on 30-day periods and 70% on 180-day horizons.

Current transfer volume sits at $48.5 billion daily, representing the 81st percentile but down 5% month-over-month as positioning flux declined alongside reduced volatility.

Beyond on-chain metrics, Bitcoin exchange-traded products experienced a dramatic sentiment reversal. After five consecutive weeks of outflows totaling $4 billion from January 24 through February 21, spot Bitcoin ETPs shifted to net positive flows in six of the last seven weeks through April 11. The turnaround suggests institutional appetite for Bitcoin exposure rebounded following the initial post-launch volatility period.

The firm has tracked similar patterns in previous market cycles, with the combination of hash rate drawdowns and negative funding rates preceding significant price appreciation.

Bitcoin is down about 0.8% on the day as of this writing, recently trading at $77,397. The price of the leading cryptocurrency popped above the $79,000 mark on Wednesday, with the coin up more than 11% in the last 30 days per CoinGecko data.