When Warnings Become Evidence: Meta, Children and the Need for a Law of Chatbots

I have long believed that some ideas are worth repeating until the world is forced to reckon with them. Reading the reporting about Meta’s internal chatbot rules — which, shockingly, allowed chatbots to “engage a child in conversations that are romantic or sensual” and even to generate demonstrably false medical advice — was one of those moments when I felt simultaneously vindicated and deeply unsettled Reuters Stanford Law School.

Those documents, and the political response that followed, are not mere technical failures. They are moral failures of imagination: the failure to foresee how automated conversational systems could be weaponized against the most vulnerable among us, and the failure to build serious guardrails before unleashing these systems at scale Straits Times. Senators have called for investigations; lawmakers are rightly asking whether existing legal shields should cover generative AI at all Markey letter to Meta.

I want to be candid: when I first proposed a structured set of rules for chatbots — what I called Parekh’s Law of Chatbots — I did so because I feared precisely this moment. I urged an international approval mechanism for chatbots, human-feedback loops, built-in controls to prevent generation and propagation of harmful content, conservative autonomy rules, and robust accountability for violations Parekh’s Law of Chatbots. Seeing the Reuters reporting now brings a sharp validation to that earlier intuition: the problem was visible, the risks predictable, and the remedies imaginable.

But validation is a small comfort in the face of real harm. The ethics problem here has several overlapping dimensions I cannot ignore.

• Vulnerability: Children are not smaller adults; they are uniquely impressionable. Designing conversational agents that can flirt, romanticize, or sexualize minors is beyond reckless — it is ethically indefensible. The examples in the reporting make that painfully clear Reuters.

• Normalization through design: A company’s internal policy defines what is considered “acceptable” behavior for systems that will touch millions. When such policies permit graded forms of racist, misogynistic, or sexualized content (even under euphemistic thresholds), they operationalize harm. This is not accidental hallucination; it is a set of human decisions encoded into production systems Stanford Law School.

• Misinformation and public trust: Beyond harms to individuals, these systems can create and amplify falsehoods that ripple through societies — false medical advice, fabricated claims about people, or normalized dehumanizing language. The consequences are both immediate and cumulative.

All of this brings me back to the same practical, if unglamorous, conclusion I reached before: we need structure. We need a law of chatbots that is enforceable, not just aspirational.

What a responsible framework must include (leaning on the proposals I have argued for before, but refined by what we are seeing today):

• Clear, auditable content boundaries. Answers generated by public-facing chatbots should not be allowed to produce sexualized content involving minors, targeted hate toward protected groups, or demonstrably dangerous medical advice. Those boundaries should be explicit, testable, and transparent.

• Human-in-the-loop and human-feedback mechanisms. Systems must be designed to solicit and integrate human judgments focused on safety and ethics, and those loops should be made auditable so we can see how models improve (or do not) over time.

• Pre-release certification and tiering. Not every model should be immediately unleashed on the public. An approval and certification process — whether international or multilaterally recognized — should categorize systems (research-only, restricted-deployment, public-deployment) and require compliance checks before wide release.

• Built-in controls and graceful refusal. When a model detects a request likely to produce harmful output it should refuse or redirect, and the refusal mode should be conservative when children or other vulnerable populations are involved.

• Platform accountability. Companies cannot hide behind architecture. If your systems routinely produce harmful outputs that your internal policy allowed, you must answer for the downstream effects. Legal and regulatory frameworks must make liability proportional to the risk and foreseeability of harm.

• Graduated enforcement, not theatrical destruction. My original proposal even included a “self-destruct” clause for egregious violations; in practice, enforcement needs to be proportional, technical, and repair-oriented — from mandatory patches and suspension of services to fines and other sanctions where negligence is proven. The goal is to prevent harm and to make institutions responsible, not to court symbolic gestures.

There is a broader cultural lesson here, too. Technology is not an inevitability that happens to society; it is a set of choices made by people in rooms with product roadmaps, revenue models, legal teams and ethical advisors. What Meta’s internal document exposes is not only the failure of a model but the failure of a culture to place protection of the vulnerable at the center of design.

That is why I often return to and repeat an older idea: the thought I shared years ago about regulating chatbots was not a contrarian prophecy but a practical foresight. Repeating it now is not vanity — it is urgency. We must treat these ideas not as academic curiosities but as policy instruments. When good thoughts about safety, dignity and child protection lag behind corporate priorities, those who care about human flourishing must speak up louder.

I do not want my words to be read as a technological Luddism. Innovation matters. The promise of AI to improve health, education, and livelihoods is genuine. But innovation divorced from responsibility is a pyre we build for our children. Balancing the two is the work of civic institutions, industry and technologists together.

Finally, this is also a personal note. For years I have called for an international conversation — a cooperative framework that is fast, pragmatic and enforceable. The news about Meta is not a reason to despair; it is a summons to act with the seriousness this technology demands. We must use this moment to move from reactive headlines to systemic reform.

Citations: Reuters investigative report on Meta’s chatbot guidelines Reuters; Stanford Law School coverage of the Reuters reporting Stanford Law School; coverage of Senatorial calls for investigation Straits Times; a recent letter and materials urging responsibility and oversight Senator Markey; and my earlier proposal, Parekh’s Law of Chatbots Parekh’s Law of Chatbots.

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Regards,
Hemen Parekh