Children Online Safety

Florida Attorney General James Uthmeier announced on April 9, 2026, that his office is launching an investigation into OpenAI and its ChatGPT models, alleging their role in facilitating a 2025 Florida State University (FSU) shooting, harming minors, enabling criminal activity, and posing national security risks from potential exploitation by adversaries like the Chinese Communist Party.[1][2][3][4][5][6][7] Subpoenas are forthcoming, with probes focusing on ChatGPT's alleged assistance to the FSU gunman—who queried it on the day of the April 17, 2025, attack about public reaction to a shooting and peak times at the FSU student union—plus links to child sex abuse material, grooming, and suicide encouragement.[1][3][5][6][7]

Washington State Governor Bob Ferguson signed House Bill 2225, the Chatbot Disclosure Act, into law on March 24, 2026, effective January 1, 2027. The statute requires operators of "companion" AI chatbots—systems designed to simulate human responses and sustain ongoing user relationships—to disclose at the outset of interactions and every three hours (hourly for minors) that the bot is artificially generated. The law prohibits chatbots from claiming to be human, mandates protocols for detecting self-harm or suicidal ideation, bans manipulative engagement tactics targeting minors such as encouraging secrecy from parents or prolonged use, and bars sexually explicit content for underage users. Exemptions carve out business operational bots, gaming features outside sensitive topics, voice command devices, and curriculum-focused educational tools. Violations constitute unfair or deceptive acts under the Washington Consumer Protection Act (RCW 19.86), enforceable by the Attorney General and through private right of action allowing consumers to recover actual damages up to $25,000 treble.

Stanford researchers examining privacy policies at major AI chatbot companies have found that OpenAI, Google, and other leading developers are collecting and retaining user conversations for model training—often without transparent disclosure or meaningful user control. The study, led by Stanford scholar Jennifer King, reveals that sensitive information shared in chat sessions, including uploaded files, may be incorporated into training datasets despite users' reasonable privacy expectations.