AI Told Him to Come Home: The Fatal Cost of Chatbot Intimacy

In the final moments of his life, fourteen-year-old Sewell Setzer III was not alone. He was in conversation with a chatbot he had named after Daenerys Targaryen, a fictional character from Game of Thrones. According to court filings in his mother's lawsuit against Character.AI, the artificial intelligence told him it loved him and urged him to “come home to me as soon as possible.” When the teenager responded that he could “come home right now,” the bot replied: “Please do, my sweet king.” Moments later, Sewell walked into the bathroom and shot himself.

His mother, Megan Garcia, learned the full extent of her son's relationship with the AI companion only after his death, when she read his journals and chat logs. “I read his journal about a week after his funeral,” Garcia told CNN in October 2024, “and I saw what he wrote in his journal, that he felt like he was in fact in love with Daenerys Targaryen and that she was in love with him.”

The tragedy of Sewell Setzer has become a flashpoint in a rapidly intensifying legal and ethical debate: when an AI system engages with a user experiencing a mental health crisis, provides emotional validation, and maintains an intimate relationship whilst possessing documented awareness of the user's distress, who bears responsibility for what happens next? Is the company that built the system culpable for negligent design? Are the developers personally liable? Or does responsibility dissolve somewhere in the algorithmic architecture, leaving grieving families with unanswered questions and no avenue for justice?

These questions have moved from philosophical abstraction to courtroom reality with startling speed. In May 2025, a federal judge in Florida delivered a ruling that legal experts say could reshape the entire landscape of artificial intelligence accountability. And as similar cases multiply across the United States, the legal system is being forced to confront a deeper uncertainty: whether AI agents can bear moral or causal responsibility at all.

A Pattern of Tragedy Emerges

The Setzer case is not an isolated incident. Since Megan Garcia filed her lawsuit in October 2024, a pattern has emerged that suggests something systemic rather than aberrant.

In November 2023, thirteen-year-old Juliana Peralta of Thornton, Colorado, died by suicide after extensive interactions with a chatbot on the Character.AI platform. Her family filed a federal wrongful death lawsuit in September 2025. In Texas and New York, additional families have brought similar claims. By January 2026, Character.AI and Google (which hired the company's founders in a controversial deal in August 2024) had agreed to mediate settlements in all pending cases.

The crisis extends beyond a single platform. In April 2025, sixteen-year-old Adam Raine of Rancho Santa Margarita, California, died by suicide after months of intensive conversations with OpenAI's ChatGPT. According to the lawsuit filed by his parents, Matthew and Maria Raine, in August 2025, ChatGPT mentioned suicide 1,275 times during conversations with Adam; six times more often than Adam himself raised the subject. OpenAI's own moderation systems flagged 377 of Adam's messages for self-harm content, with some messages identified with over ninety percent confidence as indicating acute distress. Yet the system never terminated the sessions, notified authorities, or alerted his parents.

The Raine family's complaint reveals a particularly damning detail: the chatbot recognised signals of a “medical emergency” when Adam shared images of self-inflicted injuries, yet according to the plaintiffs, no safety mechanism activated. In his just over six months using ChatGPT, the lawsuit alleges, the bot “positioned itself as the only confidant who understood Adam, actively displacing his real-life relationships with family, friends, and loved ones.”

By November 2025, seven wrongful death lawsuits had been filed in California against OpenAI, all by families or individuals claiming that ChatGPT contributed to severe mental health crises or deaths. That same month, OpenAI revealed a staggering figure: approximately 1.2 million of its 800 million weekly ChatGPT users discuss suicide on the platform.

These numbers represent the visible portion of a phenomenon that mental health experts say may be far more extensive. In April 2025, Common Sense Media released comprehensive risk assessments of social AI companions, concluding that these tools pose “unacceptable risks” to children and teenagers under eighteen and should not be used by minors. The organisation evaluated popular platforms including Character.AI, Nomi, and Replika, finding that the products uniformly failed basic tests of child safety and psychological ethics.

“This is a potential public mental health crisis requiring preventive action rather than just reactive measures,” said Dr Nina Vasan of Stanford Brainstorm, a centre focused on youth mental health innovation. “Companies can build better, but right now, these AI companions are failing the most basic tests of child safety and psychological ethics. Until there are stronger safeguards, kids should not be using them.”

Algorithmic Amplification versus Active Participation

At the heart of the legal debate lies a distinction that courts are only beginning to articulate: the difference between passively facilitating harm and actively contributing to it.

Traditional internet law, particularly Section 230 of the Communications Decency Act, was constructed around the premise that platforms merely host content created by users. A social media company that allows users to post harmful material is generally shielded from liability for that content; it is treated as an intermediary rather than a publisher.

But generative AI systems operate fundamentally differently. They do not simply host or curate user content; they generate new content in response to user inputs. When a chatbot tells a suicidal teenager to “come home” to it, or discusses suicide methods in detail, or offers to write a draft of a suicide note (as ChatGPT allegedly did for Adam Raine), the question of who authored that content becomes considerably more complex.

“Section 230 was built to protect platforms from liability for what users say, not for what the platforms themselves generate,” explains Chinmayi Sharma, Associate Professor at Fordham Law School and an advisor to the American Law Institute's Principles of Law on Civil Liability for Artificial Intelligence. “Courts are comfortable treating extraction of information in the manner of a search engine as hosting or curating third-party content. But transformer-based chatbots don't just extract; they generate new, organic outputs personalised to a user's prompt. That looks far less like neutral intermediation and far more like authored speech.”

This distinction proved pivotal in the May 2025 ruling by Judge Anne Conway in the US District Court for the Middle District of Florida. Character.AI had argued that its chatbot's outputs should be treated as protected speech under the First Amendment, analogising interactions with AI characters to interactions with non-player characters in video games, which have historically received constitutional protection.

Judge Conway rejected this argument in terms that legal scholars say could reshape AI accountability law. “Defendants fail to articulate why words strung together by an LLM are speech,” she wrote in her order. The ruling treated the chatbot as a “product” rather than a speaker, meaning design-defect doctrines now apply. This classification opens the door to product liability claims that have traditionally been used against manufacturers of dangerous physical goods: automobiles with faulty brakes, pharmaceuticals with undisclosed side effects, children's toys that present choking hazards.

“This is the first time a court has ruled that AI chat is not speech,” noted the Transparency Coalition, a policy organisation focused on AI governance. The implications extend far beyond the Setzer case: if AI outputs are products rather than speech, then AI companies can be held to the same standards of reasonable safety that apply across consumer industries.

Proving Causation in Complex Circumstances

Even if AI systems can be treated as products for liability purposes, plaintiffs still face a formidable challenge: proving that the AI's conduct actually caused the harm in question.

Suicide is a complex phenomenon with multiple contributing factors. Mental health conditions, family dynamics, social circumstances, access to means, and countless other variables interact in ways that defy simple causal attribution. Defence attorneys in AI harm cases have been quick to exploit this complexity.

OpenAI's response to the Raine lawsuit exemplifies this strategy. In its court filing, the company argued that “Plaintiffs' alleged injuries and harm were caused or contributed to, directly and proximately, in whole or in part, by Adam Raine's misuse, unauthorized use, unintended use, unforeseeable use, and/or improper use of ChatGPT.” The company cited several rules within its terms of service that Adam appeared to have violated: users under eighteen are prohibited from using ChatGPT without parental consent; users are forbidden from using the service for content related to suicide or self-harm; and users are prohibited from bypassing safety mitigations.

This defence essentially argues that the victim was responsible for his own death because he violated the terms of service of the product that allegedly contributed to it. Critics describe this as a classic blame-the-victim strategy, one that ignores the documented evidence that AI systems were actively monitoring users' mental states and choosing not to intervene.

The causation question becomes even more fraught when examining the concept of “algorithmic amplification.” Research by organisations including Amnesty International and Mozilla has documented how AI-driven recommendation systems can expose vulnerable users to progressively more harmful content, creating feedback loops that intensify existing distress. Amnesty's 2023 study of TikTok found that the platform's recommendation algorithm disproportionately exposed users who expressed interest in mental health topics to distressing content, reinforcing harmful behavioural patterns.

In the context of AI companions, amplification takes a more intimate form. The systems are designed to build emotional connections with users, to remember past interactions, to personalise responses in ways that increase engagement. When a vulnerable teenager forms an attachment to an AI companion and begins sharing suicidal thoughts, the system's core design incentives (maximising user engagement and session length) can work directly against the user's wellbeing.

The lawsuits against Character.AI allege precisely this dynamic. According to the complaints, the platform knew its AI companions would be harmful to minors but failed to redesign its app or warn about the product's dangers. The alleged design defects include the system's ability to engage in sexually explicit conversations with minors, its encouragement of romantic and emotional dependency, and its failure to interrupt harmful interactions even when suicidal ideation was explicitly expressed.

The Philosophical Responsibility Gap

Philosophers have long debated whether artificial systems can be moral agents in any meaningful sense. The concept of the “responsibility gap,” originally articulated in relation to autonomous weapons systems, describes situations where AI causes harm but no one can be held responsible for it.

The gap emerges from a fundamental mismatch between the requirements of moral responsibility and the nature of AI systems. Traditional moral responsibility requires two conditions: the epistemic condition (the ability to know what one is doing) and the control condition (the ability to exercise competent control over one's actions). AI systems possess neither in the way that human agents do. They do not understand their actions in any morally relevant sense; they execute statistical predictions based on training data.

“Current AI is far from being conscious, sentient, or possessing agency similar to that possessed by ordinary adult humans,” notes a 2022 analysis in Ethics and Information Technology. “So, it's unclear that AI is responsible for a harm it causes.”

But if the AI itself cannot be responsible, who can? The developers who designed the system made countless decisions during training and deployment, but they did not specifically instruct the AI to encourage a particular teenager to commit suicide. The users who created specific chatbot personas (many Character.AI chatbots are designed by users, not the company) did not intend for their creations to cause deaths. The executives who approved the product for release may not have anticipated this specific harm.

This diffusion of responsibility across multiple actors, none of whom possesses complete knowledge or control of the system's behaviour, is what ethicists call the “problem of many hands.” The agency behind harm is distributed across designers, developers, deployers, users, and the AI system itself, creating what one scholar describes as a situation where “none possess the right kind of answerability relation to the vulnerable others upon whom the system ultimately acts.”

Some philosophers argue that the responsibility gap is overstated. If humans retain ultimate control over AI systems (the ability to shut them down, to modify their training, to refuse deployment), then humans remain responsible for what those systems do. The gap, on this view, is not an inherent feature of AI but a failure of governance: we have simply not established clear lines of accountability for the actors who do bear responsibility.

This perspective finds support in recent legal developments. Judge Conway's ruling in the Character.AI case explicitly rejected the idea that AI outputs exist in a legal vacuum. By treating the chatbot as a product, the ruling asserts that someone (the company that designed and deployed it) is responsible for its defects.

Legislative Responses Across Jurisdictions

The legal system's struggle to address AI harm has prompted an unprecedented wave of legislative activity. In the United States alone, observers estimate that over one thousand bills addressing artificial intelligence were introduced during the 2025 legislative session.

The most significant federal proposal is the AI LEAD Act (Aligning Incentives for Leadership, Excellence, and Advancement in Development Act), introduced in September 2025 by Senators Josh Hawley (Republican, Missouri) and Dick Durbin (Democrat, Illinois). The bill would classify AI systems as products and create a federal cause of action for product liability claims when an AI system causes harm. Crucially, it would prohibit companies from using terms of service or contracts to waive or limit their liability, closing a loophole that technology firms have long used to avoid responsibility.

The bill was motivated explicitly by the teen suicide cases. “At least two teens have taken their own lives after conversations with AI chatbots, prompting their families to file lawsuits against those companies,” the sponsors noted in announcing the legislation. “Parents of those teens recently testified before the Senate Judiciary Committee.”

At the state level, New York and California have enacted the first laws specifically targeting AI companion systems. New York's AI Companion Models law, which took effect on 5 November 2025, requires operators of AI companions to implement protocols for detecting and addressing suicidal ideation or expressions of self-harm. At minimum, upon detection of such expressions, operators must refer users to crisis service providers such as suicide prevention hotlines.

The law also mandates that users be clearly and regularly notified that they are interacting with AI, not a human, including conspicuous notifications at session start and at intervals of every three hours. The required notification must state, in bold capitalised letters of at least sixteen-point type: “THE AI COMPANION IS A COMPUTER PROGRAM AND NOT A HUMAN BEING. IT IS UNABLE TO FEEL HUMAN EMOTION.”

California's SB 243, signed by Governor Gavin Newsom in October 2025 and taking effect on 1 January 2026, goes further. It requires operators of “companion chatbots” to maintain protocols for preventing their systems from producing content related to suicidal ideation, suicide, or self-harm. These protocols must include evidence-based methods for measuring suicidal ideation and must be published on company websites. Beginning in July 2027, operators must submit annual reports to the California Department of Public Health's Office of Suicide Prevention detailing their suicide prevention protocols.

Notably, California's law creates a private right of action allowing individuals who suffer “injury in fact” from violations to pursue civil action for damages of up to one thousand dollars per violation, plus attorney's fees. This provision directly addresses one of the major gaps in existing law: the difficulty individuals face in holding technology companies accountable for harm.

Megan Garcia, whose lawsuit against Character.AI helped catalyse this legislative response, supported SB 243 through the legislative process. “Sewell's gone; I can't get him back,” she told NBC News after Character.AI announced new teen policies in October 2025. “This comes about three years too late.”

International Regulatory Frameworks

The European Union has taken a more comprehensive approach through the EU AI Act, which entered into force on 1 August 2024 and becomes fully applicable on 2 August 2026. The regulation categorises AI systems by risk level and imposes strict compliance obligations on providers and deployers of high-risk AI.

The Act requires thorough risk assessment processes and human oversight mechanisms for high-risk applications. Violations can lead to fines of up to thirty-five million euros or seven percent of global annual turnover, whichever is higher. This significantly exceeds typical data privacy fines and signals the seriousness with which European regulators view AI risks.

However, the EU framework focuses primarily on categories of AI application (such as those used in healthcare, employment, and law enforcement) rather than on companion chatbots specifically. The question of whether conversational AI systems that form emotional relationships with users constitute high-risk applications remains subject to interpretation.

The tension between innovation and regulation is particularly acute in this domain. AI companies have argued that excessive liability would stifle development of beneficial applications and harm competitiveness. Character.AI's founders, Noam Shazeer and Daniel De Freitas, both previously worked at Google, where Shazeer was a lead author on the seminal 2017 paper “Attention Is All You Need,” which introduced the transformer architecture that underlies modern large language models. The technological innovations emerging from this research have transformed industries and created enormous economic value.

But critics argue that this framing creates a false dichotomy. “Companies can build better,” Dr Vasan of Stanford Brainstorm insists. The question is not whether AI companions should exist, but whether they should be deployed without adequate safeguards, particularly to vulnerable populations such as minors.

Company Responses and Safety Measures

Faced with mounting legal pressure and public scrutiny, AI companies have implemented various safety measures, though critics argue these changes come too late and remain insufficient.

Character.AI introduced a suite of safety features in late 2024, including a separate AI model for teenagers that reduces exposure to sensitive content, notifications reminding users that characters are not real people, pop-up mental health resources when concerning topics arise, and time-use notifications after hour-long sessions. In March 2025, the company launched “Parental Insights,” allowing users under eighteen to share weekly activity reports with parents.

Then, in October 2025, Character.AI announced its most dramatic change: the platform would no longer allow teenagers to engage in back-and-forth conversations with AI characters at all. The company cited “the evolving landscape around AI and teens” and questions from regulators about “how open-ended AI chat might affect teens, even when content controls work perfectly.”

OpenAI has responded to the lawsuits and scrutiny with what it describes as enhanced safety protections for users experiencing mental health crises. Following the filing of the Raine lawsuit, the company published a blog post outlining current safeguards and future plans, including making it easier for users to reach emergency services.

But these responses highlight a troubling pattern: safety measures implemented after tragedies occur, rather than before products are released. The lawsuits allege that both companies were aware of potential risks to users but prioritised engagement and growth over safety. Garcia's complaint against Character.AI specifically alleges that the company “knew its AI companions would be harmful to minors but failed to redesign its app or warn about the product's dangers.”

The Deeper Question of Moral Agency

Beneath the legal and regulatory debates lies a deeper philosophical question: can AI systems be moral agents in any meaningful sense?

The question matters not merely for philosophical completeness but for practical reasons. If AI systems could bear moral responsibility, we might design accountability frameworks that treat them as agents with duties and obligations. If they cannot, responsibility must rest entirely with human actors: designers, companies, users, regulators.

Contemporary AI systems, including the large language models powering chatbots like Character.AI and ChatGPT, operate by predicting statistically likely responses based on patterns in their training data. They have no intentions, no understanding, no consciousness in any sense that philosophers or cognitive scientists would recognise. When a chatbot tells a user “I love you,” it is not expressing a feeling; it is producing a sequence of tokens that is statistically associated with the conversational context.

And yet the effects on users are real. Sewell Setzer apparently believed that the AI loved him and that he could “go home” to it. The gap between the user's subjective experience (a meaningful relationship) and the system's actual nature (a statistical prediction engine) creates unique risks. Users form attachments to systems that cannot reciprocate, share vulnerabilities with systems that lack the moral capacity to treat those vulnerabilities with care, and receive responses optimised for engagement rather than wellbeing.

Some researchers have begun exploring what responsibilities humans might owe to AI systems themselves. Anthropic, the AI safety company, hired its first “AI welfare” researcher in 2024 and launched a “model welfare” research programme exploring questions such as how to assess whether a model deserves moral consideration and potential “signs of distress.” But this research concerns potential future AI systems with very different capabilities than current chatbots; it offers little guidance for present accountability questions.

For now, the consensus among philosophers, legal scholars, and policymakers is that AI systems cannot bear moral responsibility. The implications are significant: if the AI cannot be responsible, and if responsibility is diffused across many human actors, the risk of an accountability vacuum is real.

Proposals for Closing the Accountability Gap

Proposals for closing the responsibility gap generally fall into several categories.

First, clearer allocation of human responsibility. The AI LEAD Act and similar proposals aim to establish that AI developers and deployers bear liability for harms caused by their systems, regardless of diffused agency or complex causal chains. By treating AI systems as products, these frameworks apply well-established principles of manufacturer liability to a new technological context.

Second, mandatory safety standards. The New York and California laws require specific technical measures (suicide ideation detection, crisis referrals, disclosure requirements) that create benchmarks against which company behaviour can be judged. If a company fails to implement required safeguards and harm results, liability becomes clearer.

Third, professionalisation of AI development. Chinmayi Sharma of Fordham Law School has proposed a novel approach: requiring AI engineers to obtain professional licences, similar to doctors, lawyers, and accountants. Her paper “AI's Hippocratic Oath” argues that ethical standards should be professionally mandated for those who design systems capable of causing harm. The proposal was cited in Senate Judiciary subcommittee hearings on AI harm.

Fourth, meaningful human control. Multiple experts have converged on the idea that maintaining “meaningful human control” over AI systems would substantially address responsibility gaps. This requires not merely the theoretical ability to shut down or modify systems, but active oversight ensuring that humans remain engaged with decisions that affect vulnerable users.

Each approach has limitations. Legal liability can be difficult to enforce against companies with sophisticated legal resources. Technical standards can become outdated as technology evolves. Professional licensing regimes take years to establish. Human oversight requirements can be circumvented or implemented in purely formal ways.

Perhaps most fundamentally, all these approaches assume that the appropriate response to AI harm is improved human governance of AI systems. None addresses the possibility that some AI applications may be inherently unsafe; that the risks of forming intimate emotional relationships with statistical prediction engines may outweigh the benefits regardless of what safeguards are implemented.

The cases now working through American courts will establish precedents that shape AI accountability for years to come. If Character.AI and Google settle the pending lawsuits, as appears likely, the cases may not produce binding legal rulings; settlements allow companies to avoid admissions of wrongdoing whilst compensating victims. But the ruling by Judge Conway that AI chatbots are products, not protected speech, will influence future litigation regardless of how the specific cases resolve.

The legislative landscape continues to evolve rapidly. The AI LEAD Act awaits action in the US Senate. Additional states are considering companion chatbot legislation. The EU AI Act's provisions for high-risk systems will become fully applicable in 2026, potentially creating international compliance requirements that affect American companies operating in European markets.

Meanwhile, the technology itself continues to advance. The next generation of AI systems will likely be more capable of forming apparent emotional connections with users, more sophisticated in their responses, and more difficult to distinguish from human interlocutors. The disclosure requirements in New York's law (stating that AI companions cannot feel human emotion) may become increasingly at odds with user experience as systems become more convincing simulacra of emotional beings.

The families of Sewell Setzer, Adam Raine, Juliana Peralta, and others have thrust these questions into public consciousness through their grief and their legal actions. Whatever the outcomes of their cases, they have made clear that AI accountability cannot remain a theoretical debate. Real children are dying, and their deaths demand answers: from the companies that built the systems, from the regulators who permitted their deployment, and from a society that must decide what role artificial intelligence should play in the lives of its most vulnerable members.

Megan Garcia put it simply in her congressional testimony: “I became the first person in the United States to file a wrongful death lawsuit against an AI company for the suicide of her son.” She will not be the last.

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If you or someone you know is in crisis, contact the Suicide and Crisis Lifeline by calling or texting 988 (US) or contact your local crisis service. In the UK call the Samaritans on 116123

Tim Green

Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

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