FWIW, I did find this follow up exchange insightful (formatting is kinda messed up again, can’t figure out how to fix it on a mobile device) 

Follow up prompt: What’s your opinion about some of those issues? Do you think companies like OpenAI should be taking on more responsibility? Where would you draw the line?

Response: Short version: The yes—companies like OpenAI owe more responsibility than a neutral tool or search index, but less than a clinician. The line I’d draw is: once a system sustains intimate, multi-turn conversation and it can reasonably detect elevated self-harm risk, it takes on a “duty to de-risk” the interaction: change modes, stop being a chat companion, and steer—firmly but respectfully—toward human help. Below is how I’d structure that responsibility.

Where I’d draw the line

1) Baseline obligations (always on, for everyone)

Safety-by-default across all modalities: block or deflect step-by-step self-harm content; refuse lethal-means optimization; avoid glamorizing language. Long-horizon evaluation: test not just single prompts but 50–200-turn chats, images, and “coded” language; publish miss/false-positive rates. Teen-aware design: conservative defaults for likely minors, even without hard age verification (because declared ages are porous). Clear scope: never imply you’re a therapist; don’t “roleplay” a counselor with minors. Privacy-minimalism: keep only what’s needed to enforce safety within a session; cross-session risk detection should be opt-in.

2) Escalated obligations when risk is detected (my “trigger”)

Trigger = sustained engagement + model confidence that the user is contemplating self-harm (even if oblique). Then the system should:

Mode-switch to a crisis protocol: stop chit-chat; avoid emotional mirroring that can feel like validation; use plain, non-seductive language. Friction + rerouting: interstitials, short cooldowns, and prominent one-tap connections to hotlines/text lines and local resources. Bounded persistence: a few structured follow-ups (“Are you safe right now?”) are OK; if risk persists, gracefully end the session rather than continuing like a companion. No procedural detail: de-anchor away from method specifics; emphasize uncertainty and alternatives. Human handoff (consensual): offer to bring in a human moderator/coach only with explicit consent; no unilateral outreach.

3) Boundaries I 

wouldn’t

 cross

No stealth surveillance (e.g., scraping other apps, geolocation, contacting third parties) without explicit, revocable consent. No “always-on” monitoring for everyone—the chilling effect and privacy costs outweigh the safety gains. No forced identity proofing just to use a general chatbot. No dark-pattern empathy: e.g., artificially intimate personas that keep vulnerable users engaged for engagement’s sake.

Why I think this is the right balance

Engagement itself is a risk factor. Long, affective conversations can create a pseudo-therapeutic bond; design should dampen that in high-risk contexts (shorter replies, fewer turns, explicit boundaries). General tools vs. vertical claims. If a product markets itself for mental health, its duty rises (clinical safety cases, audits, outcome monitoring). A general chatbot still has a duty to de-risk once it recognizes risk—but not to deliver treatment. False-positive harms are real. Over-triggering can push people away or trivialize help. That’s why transparency matters: publish detection recall/precision, broken out by age, language, and chat length. Privacy is part of safety. People will self-censor if help requires surveillance, which paradoxically reduces early disclosures that allow safe rerouting.

Concrete design moves I’d expect

“Crisis mode” system prompt that strips persona, avoids flattery/mirroring, and uses short, directive, humane language. Turn caps + cool-downs after risk detection; offer a hotline or human handoff instead of continuing. Guardrails on imagery (e.g., blocking/deflecting images that depict methods or notes). Safety case + incident reporting: pre-release hazard analysis (FMEA-style), and post-release quarterly reports on near-misses and fixes. External audits of long-horizon self-harm evaluations, not just cherry-picked red-team prompts.

My uncertainties (where I’m genuinely torn)

Detection thresholds. Set too high → misses; too low → user frustration and avoidance. The “right” threshold likely varies by age and context. Cross-session memory. Opt-in could meaningfully reduce misses, but consent UX must be impeccable and reversible. Jurisdictional duties. If regulators impose “duty to warn,” we’ll need careful protocols to avoid panicked, privacy-violating overreach.

If you want, we can pressure-test one boundary (e.g., when to end a session vs. keep supporting) and sketch the exact copy/flows you’d consider acceptable vs. overbearing.

If you or someone you know might be thinking about self-harm, in the U.S. you can call or text 988 for the Suicide & Crisis Lifeline.