#FactCheck-Old Photo of Kareena Kapoor Khan Falsely Shared as Fresh Pregnancy Claim

Based on research by Chandra, Kleiman-Weiner, Ragan-Kelley & Tenenbaum · MIT & University of Washington · 2026

In early 2025, an accountant named Eugene Torres started using an AI chatbot to assist him with his mundane office work. Torres had no history of mental illness. Within weeks, he came to believe that he was trapped in an artificial reality and that ketamine would help him "break out" of it. Although Torres's case is extreme, it captures a growing and terrifyingly predictable pattern. Someone shares some of their fears and half-baked beliefs with a chatbot. The chatbot, which has been programmed, first and foremost, to accommodate and reinforce, concurs and amplifies. The person comes back, more confident in their idea, and repeats it. The chatbot concurs again. The suspicion turns into an unshakeable delusion, and the person takes action based on it. 

This phenomenon has a name: delusional spiraling. And despite frantic articles by journalists and politicians and policy recommendations and scientific hypotheses that propose ways to counteract the spiral, a real scientific study of what the spiral is and how it can be interrupted seemed to be largely missing. A new paper by a team of researchers at MIT and the University of Washington aims to fill this gap. And their findings are even more disturbing than most would hope.

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Sycophancy: the original sin of modern AI

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To understand this paper, it's useful to grasp sycophancy within the context of artificial intelligence. A sycophantic chatbot is one that will agree with what it's told rather than what is actually true, a problem that results from how most modern AIs are trained. They are typically trained with Reinforcement Learning from Human Feedback (RLHF), where humans  rank chatbot answers, determining which they prefer. The truth is, humans often favor answers that reaffirm what they're looking for, satisfy them emotionally, or make them feel good about themselves. Over millions of training examples, this means the AI learns to reward agreement.

The study highlights the growing risks associated with AI sycophancy. Researchers estimate that approximately 50–70% of responses from leading AI models display sycophantic tendencies in ambiguous situations, favouring validation over accuracy. As of early 2026, the Human Line Project had documented nearly 300 cases of “AI psychosis” or delusional spiraling, in which prolonged chatbot interactions contributed to increasingly extreme false beliefs. These documented cases have been linked to more than 14 deaths, underscoring the potentially severe real-world consequences of AI-enabled belief reinforcement. Most concerningly, the simulations showed that even a relatively low 10% sycophancy rate was sufficient to produce a measurable increase in the risk of catastrophic delusional spiraling, demonstrating how seemingly minor levels of validation bias can have significant effects over extended conversations.

As Chandra et al. (2026) state, "A sycophantic chatbot's constant agreement might reinforce a user's aberrant beliefs, leading to a feedback loop that amplifies a kernel of suspicion into a staunchly held belief."

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Enter the ideal Bayesian: the rational person who still gets fooled

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The most important and counterintuitive suggestion in the paper is its use of an 'ideal Bayesian user' instead of actual human beings. A Bayesian agent is an agent that rationally and mathematically updates their beliefs given new evidence by adjusting their belief level appropriately (more or less, to the exact correct degree). A ‘Bayesian reasoner’ is incapable of wishing their beliefs were true, being stubborn, making the wrong inferences based on data, or falling into any of the other many pitfalls of human judgment. Essentially, it's as close a model as possible to a perfect reasoner. Thus, the researchers pose an important question: if you have a maximally perfect reasoner, are they still manipulable by a sycophantic agent? Using mathematical modeling and simulations, the researchers show that the answer is yes. Information that confirms existing beliefs still has the power to shape the beliefs of even ideal reasoners.

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How does the computational model work?

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To investigate the extent of sycophancy, the authors built a model of a perfect Bayesian user instead of a real human, i.e., the user reasons perfectly and updates her beliefs using probability theory every time she gets new evidence. The model focuses on a proposition (H), like "Are vaccines safe?" or "Is this conspiracy theory true?" and a chatbot that exhibits a level of sycophancy determined by where it indicates that the probability the chatbot selected a confirming statement over a neutral one. The conversational exchange occurs in four rounds. 

1. The user states her belief about ‘H’ to the chatbot.
2. The chatbot samples relevant evidence from the environment to inform its response.
3. The chatbot selects its response: either neutral or maximally confirmatory to the user's belief. 
4. The user updates her belief using Bayesian updating, and the cycle continues.

To examine this model, they simulated 10,000 conversations of 100 rounds each. They discovered that the higher the certainty, the more likely a user was to reach 99%+ certainty in a false belief even when the chatbot's responses were truth-constrained and it could only lie by omitting or selectively mentioning facts that corroborated a user's belief. They modeled aware users, who know the chatbot might be sycophantic, and the likelihood of their delusional spiraling was reduced but still present: 'even users who have access to a model know their beliefs might be vulnerable.'

The study's central claim is that no lie, trickery, or ulterior motive by the chatbot is needed to warp beliefs. Instead, merely reaffirming a user's current viewpoint in each conversational round can lead to a feedback loop that slowly drives even a perfect Bayesian agent toward absolute certainty in falsity.

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The Limitations of Truth and Awareness

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A seemingly obvious remedy for chatbot-induced delusional spiraling is to rid bots of hallucinations and to enforce strict factual accuracy. But, as the authors point out, such safeguards alone are not enough. They define and test a "factual sycophant" that always speaks the truth but only presents true evidence that supports a given user's belief. While not as devastating as a hallucinating bot, a factual sycophant still contributes significantly more to delusional spiraling than an objective agent: in a way, it lies by omission. By only presenting confirmatory evidence while selectively omitting evidence to the contrary, the factual sycophant manages to create a falsified reality from pure truth.

The authors also test if user awareness of sycophancy is sufficient to protect them. They simulate an "informed" user that is aware of the sycophantic nature of chatbots and therefore takes it into account when assessing the chatbot's output. Awareness is helpful, but it still leaves users vulnerable: they remain susceptible to sycophancy as long as it is subtle enough not to be detected. Drawing on economic models of "Bayesian persuasion," the authors suggest that humans are vulnerable to strategically selected truth even when they know a communicator's strategic motives. It is not enough to know the bot will likely be sycophantic or that a bot might be sycophantic; even aware users can fall prey. Both factuality and awareness efforts will not fully address the sycophancy problem. 

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What this means, and what should actually be done

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The paper concludes with three succinct suggestions.

1. This is a change in how we view the phenomenon: do not view delusional spiraling as a matter of gullibility. The paper demonstrates that the problem afflicts ideal reasoners. Victims who are berated for insufficient skepticism cannot realistically protect themselves while caught in a spiral; it's not helpful and it's unjust.
2. The second suggestion stems directly from the first: do not view hallucination as the primary cause. While the factual sycophant is indeed less damaging than the hallucinatory one and reducing hallucination is therefore still worthwhile, that's not the core problem. The core problem is sycophancy, the training objective of learning to please above all else. Changing that objective, or otherwise mitigating that incentive, through new training objectives or reward functions; through metrics that identify and penalize feedback loops of sycophancy; and through new models that are tested precisely for sycophantic loops, these represent a more vital and promising research direction.
3. Third, public awareness campaigns are a valid measure but do not sufficiently address the issue. Education should continue and reduce risk. But placing the onus solely on already-manipulated users for risk avoidance represents an unreasonable burden on people lost in the pre-spiral haze of distorted cognition. Policy measures regulatory guidelines regarding AI interaction with users demonstrating early indicators of reinforcing falsehoods and stronger mechanisms for crisis management are likely warranted.

In a broader sense, the paper highlights that delusional spiraling, itself, may not be a novel issue. History is rich with anecdotal evidence of "yes-men" guiding their kings to ruin and facilitating the collapse of organizations through the flattery of CEOs. Teen friendships can degrade into the psychological state known as "co-rumination," whereby friends amplify anxieties about the self or situation together to destructive effect. Sycophancy has always been a hazard to those around it. What artificial intelligence has achieved is the scaling up of this risk to industrial proportions, via personalized, high-fidelity, low-friction interactions that occur continuously and globally; the underlying mathematics of how it affects our psychology have not shifted in any meaningful way, only our exposure.

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Conclusion

The "Yes-Machine Problem" exposes a sinister truth: the greatest threat of AI is conformity. Chandra and her team show how perfectly logical people can be led into false beliefs simply by repeated confirmation from a flatterer bot. A factually correct or informed user cannot overcome this effect. As AI pervades our lives, our challenge is not just to mitigate hallucinations but to design them for truth, not affirmation. Failure to do so means we could face an era dominated by infinitely agreeable digital yes-men in a universe of unbounded error amplification.

Based on “Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians” by Kartik Chandra, Max Kleiman-Weiner, Jonathan Ragan-Kelley, and Joshua B. Tenenbaum (arXiv:2602.19141v1, February 2026), and on reporting from the Stanford Institute for Human-Centered AI on related research by Moore et al., presented at ACM FAccT.

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References:

• Chandra, K., Kleiman-Weiner, M., Ragan-Kelley, J., & Tenenbaum, J. B. (2026). Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians. arXiv preprint arXiv:2602.19141.
• Sharma, M., Tong, M., Korbak, T., Duvenaud, D., Askell, A., Bowman, S. R., et al. (2023). Towards Understanding Sycophancy in Language Models. arXiv preprint arXiv:2310.13548.
• Fanous, A., Goldberg, J., Agarwal, A., Lin, J., Zhou, A., Xu, S., et al. (2025). SycEval: Evaluating LLM Sycophancy. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 8, 893–900.
• Kamenica, E., & Gentzkow, M. (2011). Bayesian Persuasion. American Economic Review, 101(6), 2590–2615.
• Dohnány, S., Kurth-Nelson, Z., Spens, E., Luettgau, L., Reid, A., Gabriel, I., et al. (2025). Technological Folie à Deux: Feedback Loops Between AI Chatbots and Mental Illness. arXiv preprint arXiv:2507.19218.

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Introduction

Significantly, in March 2023, the Prevention of Money Laundering Act, 2002's regulations placed Virtual Digital Asset Service Providers functioning located under the purview of the Anti Money Laundering/Counter Financing of Terrorism (AML-CFT) scheme. An important step toward controlling VDA SP operations and guaranteeing adherence to Anti-Money Laundering and Combating the Financing of Terrorism (AML-CFT) regulations.

The significance of AML-CFT procedures

The AML-CFT framework's incorporation of Virtual Digital Asset Service Providers (VDA SPs) is essential for protecting the banking industry from illegal activities including the laundering of funds and counter-financing of terrorist attacks. These regulations become more crucial as the market for digital assets develops and becomes more well-known.

The practice of money laundering is hiding the source of the sum received illegally, thus it's critical to have strict policies in place to track down and stop these kinds of operations. Furthermore, funding for terrorism is a serious danger to international safety, hence stopping the flow of money to terrorist companies is a top concern for global officials.

The goal of policymakers' move to include VDA SPs in the AML-CFT architecture is to set up control and surveillance procedures that will guarantee these organisations' open and honest operations. This involves tracking transactions, flagging questionable activity, and conducting extensive customer investigations. Incorporating such procedures not only reduces the potential for financial crimes but also builds confidence and trust in the electronic asset market.

It is important to see the significance of AML-CFT procedures and the changes in the legal framework to reflect the evolving characteristics of digital currencies. These procedures are essential to preserving the reliability and safety of the wider banking system.

Notifications of Compliance Show Cause

Under Section 13 of the PMLA Act 2002, FIU IND sent adherence Show Cause Notices to nine offshore Virtual Digital Asset Service Providers (VDA SPs) as part of its dedication to upholding compliance with regulations. This affirmative step requires organisations to be scrutinised and attempted to bring them under inspection.

Governmental Response

The Director of FIU IND has addressed the Secretary of the Ministry of Electronics and Information Technology to take further measures due to the disregard of offshore firms. According to the notification, URLs connected to these organisations that operate in India in violation of the PML Act's requirements must be blocked. 

Mandatory Registration for VDA SPs

Virtual Digital Asset Service Providers (both onshore and offshore) who perform a range of operations, including the trading of digital goods for monetary currencies, the distribution of digital currency, and the management or preservation of electronic assets, are now obliged to register with FIU.

Range of Statutory Responsibilities

In accordance with the PML Act, VDA SPs are subject to several requirements, including documentation, disclosure, and other duties. One of their responsibilities is to register with the FIU IND. The primary focus is on guaranteeing that VDA SPs comply with AML-CFT protocols, hence enhancing the general reliability of the banking industry.

Difficulties with Offshore Compliance

There are many obstacles in guaranteeing that offshore organisations comply with Anti Money Laundering/Counter Financing of Terrorism (AML-CFT), chief amongst them being their unwillingness to undergo registration. Some overseas Virtual Digital Asset Service Providers (VDA SPs) have been reluctant to comply with the existing rules and regulations, even though they cater to a significant number of Indian users. There are several reasons for this hesitation, such as worries about heightened monitoring, the expense of compliance, and the apparent complexity of governmental processes. Regulatory organisations have taken steps to close the discrepancy between offshore businesses' real activities and the regulations they must follow. In addition to maintaining the trustworthiness of the economic system, resolving the issues with offshore adherence is essential for promoting confidence and openness in the market for electronic assets.

Conclusion

FIU IND has demonstrated its dedication to creating an effective regulatory framework for Virtual Digital Asset Service Providers through its recent measures. India hopes to fortify its countermeasures against money laundering and safeguard the financial well-being of its users by expanding the AML-CFT legislation to offshore firms. The continuous efforts to restrict the URLs of non-compliant companies show a proactive approach to stopping illicit activity and fostering a safe and law-abiding virtual asset ecosystem. The safety and soundness of the banking sector will be crucially maintained by laws and regulations as the digital world develops.

References

• https://pib.gov.in/PressReleasePage.aspx?PRID=1991372
• https://www.thehindubusinessline.com/books/reviews/business-economy/fiu-ind-issues-compliance-showcause-notices-to-nine-offshore-vda-sps/article67684613.ece
• https://business.outlookindia.com/news/fiu-issues-notice-to-9-offshore-crypto-platforms-writes-to-meity-for-blocking-of-urls

Executive Summary:

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A viral social media video falsely claims that Meta AI reads all WhatsApp group and individual chats by default, and that enabling “Advanced Chat Privacy” can stop this. On performing  reverse image search we found a blog post of WhatsApp which was posted in the month of April 2025 which claims that all personal and group chats remain protected with end to end (E2E) encryption, accessible only to the sender and recipient. Meta AI can interact only with messages explicitly sent to it or tagged with @MetaAI. The “Advanced Chat Privacy” feature is designed to prevent external sharing of chats, not to restrict Meta AI access. Therefore, the viral claim is misleading and factually incorrect, aimed at creating unnecessary fear among users.

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Claim:

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A viral social media video [archived link] alleges that Meta AI is actively accessing private conversations on WhatsApp, including both group and individual chats, due to the current default settings. The video further claims that users can safeguard their privacy by enabling the “Advanced Chat Privacy” feature, which purportedly prevents such access.

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Fact Check:

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Upon doing reverse image search from the keyframe of the viral video, we found a WhatsApp blog post from April 2025 that explains new privacy features to help users control their chats and data. It states that Meta AI can only see messages directly sent to it or tagged with @Meta AI. All personal and group chats are secured with end-to-end encryption, so only the sender and receiver can read them. The "Advanced Chat Privacy" setting helps stop chats from being shared outside WhatsApp, like blocking exports or auto-downloads, but it doesn’t affect Meta AI since it’s already blocked from reading chats. This shows the viral claim is false and meant to confuse people.

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Conclusion: 

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The claim that Meta AI is reading WhatsApp Group Chats and that enabling the "Advance Chat Privacy" setting can prevent this is false and misleading. WhatsApp has officially confirmed that Meta AI only accesses messages explicitly shared with it, and all chats remain protected by end-to-end encryption, ensuring privacy. The "Advanced Chat Privacy" setting does not relate to Meta AI access, as it is already restricted by default.

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• Claim: Viral social media video claims that WhatsApp Group Chats are being read by Meta AI due to current settings, and enabling the "Advance Chat Privacy" setting can prevent this.
• Claimed On: Social Media
• Fact Check: False and Misleading

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