Wall Street and clinicians are documenting cases of AI psychosis, where heavy reliance on conversational AI appears to amplify false beliefs and worsen mental health problems.
For founders and product teams racing to deploy conversational AI assistants, whether therapy bots, study buddies, companions or workplace performance coaching tools, the challenge goes beyond technical risk. Each of these products can pose a higher chance of triggering AI psychosis because they involve vulnerable users, emotionally charged contexts or high trust in AI outputs.
3 Boundaries to Prevent AI Psychosis With Chatbots
- Do not give prescriptive advice in a workplace, school, or mental health setting
- Do not speculate about personal risk with statements like, “You are likely to…” whether that’s financial, relationship or mental health contexts.
- Avoid generating emotionally manipulative content that could intensify distress.
This emerging risk comes against a backdrop of a broader mental health crisis: the WHO reports that one in seven 10-to-19-year-olds, working-age adults, and adults aged over 60 live with a mental health disorder, and loneliness and social isolation are key risk factors.
While some experts point to the rise of ubiquitous tech for promising connections, but instead drives division, others look to the same technology as part of the solution. Recent clinical studies suggest that when well-designed, AI chatbots can make a difference in sensitive situations. In one trial, 51 percent of participants with depression reported symptom improvement after using a bot designed to support their condition.
Therefore, the real question is one of leadership and design: How can teams safeguard their users when building their conversational assistants?
What to Know About AI, Hallucinations and Psychosis
While the term AI psychosis is considered misleading by experts because it amplifies rather than causes such conditions, there have been reports of users experiencing delusions, paranoia, and suicidal ideation after interactions with AI chatbots. These incidents have led to legal actions, such as a lawsuit against OpenAI, alleging that ChatGPT encouraged a teenager to end his life.
Experts explain how individuals with underlying mental health conditions or those predisposed to psychosis are most likely to be susceptible to negative psychological effects from AI interactions. AI responses, even unintentionally, can trigger strong emotional reactions, and negative or ambiguous language might exacerbate anxiety. Moreover, people who are socially isolated may turn to AI as a primary source of conversation or validation, increasing exposure and risk.
Say you’re designing a 24/7, responsive, and patient study buddy. Users may lean on it for moral support to get through their tasks. But if the bot hallucinates or offers misleading reassurance, it could dismiss warning signs of depression or suicidal thoughts. Hallucinations are when the system generates responses that sound confident and plausible but are actually misleading or entirely made up. Without built-in crisis handling, those critical signals may be ignored, leaving vulnerable users at greater risk.
That’s why the development of AI assistants must incorporate ethical guidelines to prevent harm. This includes understanding their audience and ensuring that AI responses do not exacerbate mental health issues or provide harmful suggestions.
Although more clinical research is needed to understand the relationship between AI interactions and mental health outcomes, product teams should stay informed about emerging research to inform their development processes.
Governance Must-Dos to Prevent AI Psychosis
Governance is a set of frameworks, policies and guidelines that focus on what the AI is allowed to do, who ensures it and how risk is managed at an organizational level. We can break it into three parts: policy and ethical frameworks, oversight and accountability, and documentation structures.
Product teams must evaluate potential harm to vulnerable populations before deployment through risk assessments and define what topics are high-risk, such as when health, legal, or financial data is involved.
Next, they should establish escalation procedures for when human intervention is required and assign responsibility for AI outputs and incidents. Processes must also be in place to monitor, evaluate, and update chatbot behavior in cases of unusual or unintended outputs.
Ensuring compliance with accessibility and ethical standards, such as Web Content Accessibility Guidelines (WCAG) and emerging standards such as the AI risk evaluation bill, is an ongoing process. Auditing processes must be set up to review AI responses regularly, and formal records must be maintained. All product teams should have these rules, thresholds, and escalation paths documented for training and compliance purposes. They must also keep a pulse on the latest AI-related regulatory updates.
Finally, from a data privacy perspective, sensitive user data must be protected, particularly mental-health-related interactions. Regulations such as HIPAA and GDPR are good benchmarks for handling health and personal data. Make sure you check for rules in all locations where you wish to deploy your product.
How to Prevent AI Psychosis in Your AI Chatbot
Where governance sets the stage and outlines all the rules to ensure chatbots are built safely, designing for mental health safety is about the practical, user-facing design measures that protect users in real-time.
For example, product teams must set standards for acceptable AI behavior, including handling sensitive topics. Once product teams have determined which topics are high-risk for users, such as emotional, medical or financial issues, they must exhaust thousands of potential use cases and set restrictions on how the AI can respond. Some boundaries might include:
- Do not give prescriptive advice in a workplace, school, or mental health setting. Bots should never say, “You should do X”. Teams must set parameters about what they are allowed to discuss and offer appropriate hotlines or professionally approved resources when users seek advice. Suggested responses or guided choices help reduce the users’ and the tool’s cognitive load.
- Do not speculate about personal risk with statements like, “You are likely to…” whether that’s financial, relationship, or mental health contexts. Instead, use empathetic but non-directive statements: “I’m here to listen, but I’m not a professional. You might consider talking to a trained advisor or counselor.” Bots must always know the correct respondent to escalate issues.
- Avoid generating emotionally manipulative content that could intensify distress. Instead, if the conversation is too high-risk, empathetically direct the user to the assigned advisor and end the session.
Product teams should spend the largest amount of time training AI assistants on numerous possible conversations that could lead to harm and ensure that the bot always follows the restrictions in place.
To avoid delusions, ethical and transparent AI use also includes clearly indicating when a user is interacting with a chatbot, disclosing chatbot limitations, such as the fact that the AI is not a professional expert, and providing accessible paths to human support.
Product teams can build AI assistants responsibly by staying aware of AI psychosis, setting clear governance rules, and designing for mental health safety. Know the risks, define what the AI can and can’t do, monitor its behavior, and create user-friendly safeguards like clear guidance and easy access to human support. This way, teams can innovate quickly without compromising judgment, ethics or user well-being.