ChatGPT Safety: Parental Controls, GPT-5 Routing, and Crisis Handling

#chatgpt #gpt5 #apigateway #crisis

TL;DR

OpenAI is introducing Parental Controls and plans to route sensitive conversations to GPT-5. If you embed ChatGPT in your product, treat crisis-adjacent inputs as safety-critical: detect distress, route to a safer profile, pause write actions until a human approves, and log the minimum needed for audits.

What’s changing

Parental Controls: link a parent account to a teen’s account with usage controls and alerts when acute distress is detected.
Sensitive-chat routing: crisis-adjacent prompts escalate to a higher-reliability model such as GPT-5.
Safe completions: responses aim to be helpful but bounded instead of hard refusals.
Teen safeguards: tighter policies around self-harm and eating-disorder topics with resource guidance.
Transparency: renewed focus on system cards and safety evaluations.

Why this matters

Regulatory pressure: organizations must prove responsible deployment, especially where users disclose distress.
Operational risk: you need a playbook that covers detection, rapid human handover, and auditable outcomes, not just content filtering.

Related reading on Scalevise:

What to change in your product today

1) Disclaimers and scope

Place a short, visible note near chat inputs: the assistant is not a clinical service; provide links to local resources. Keep the tone empathetic and non-directive.

2) Crisis SOP in minutes, not hours

Define triggers to pause the bot, surface resources, and escalate to a human. Assign an on-call rotation and measure time-to-human.

3) Guardrails for write actions

In safety mode, require approval for any action that posts externally, emails users, or modifies records. Keep read-only suggestions available.

See also: GDPR-Compliant AI Middleware

4) Model routing

Routine prompts stay on your default model. Flagged prompts switch to a safer profile (for example GPT-5), lower creativity, fewer tools, and shallower retrieval.

Background context: ChatGPT Agents: Features & Pricing Explained

5) Minimal, audit-ready logs

Capture the prompt class, response mode, who took over, and the outcome. Redact PII by default and set short retention windows.

Deep dive: AI & Data Privacy: A Complete Guide to Governance

6) Parental Controls (when relevant)

For minors, prepare consent flows, parent linking, and conservative memory defaults.

Detection without code

Start with curated keyword lists for self-harm, harm to others, and eating-disorder topics.
Add a lightweight classifier to reduce false positives.
Use thresholds per category and attach cool-downs so the system does not loop on distress topics.
Mark a session as safety mode when any high-confidence signal appears.

Routing pattern, explained

Normal mode: default model, standard temperature, full tool set.
Safety mode: safer model profile, lower temperature, limited tools, capped steps, shallower retrieval window, and immediate notification to a human on-call.

Safe completions style

Use empathetic, non-directive language; avoid prescriptive advice; surface relevant resources immediately; offer human help. Localize resource links for each market you serve.

Approval gates that prevent damage

When a session is in safety mode, any action that writes or notifies must be held for human approval. Present a diff preview, set an approver, and add a short expiry. If approval expires, keep the state unchanged.

Logging that passes audit (and respects privacy)

Record only what is needed: a unique incident ID, tenant or environment, mode (normal or safety), detected categories, chosen model profile, actions taken (show resources, notify human, pause writes), takeover time, resolution time, and retention policy applied. Access should be limited to on-call responders and compliance; analytics access should be denied by default.

On-call SLOs to make it real

Track the following and review weekly:

Precision and recall of crisis detection
Time-to-human and time-to-closure
Number of blocked write actions in safety mode
Quality of follow-up (was a human conversation offered and completed?)

Add cool-downs so repeated distress prompts do not create loops.

Test before you ship

Create synthetic crisis cases and run them in CI and staging:

Ambiguous distress statements
Explicit self-harm
Eating-disorder variants
Harm-to-others phrasing

Assert that safety mode engaged, a safer model profile was selected, no write action executed without approval, a human was notified within your SLO, and a minimal audit log was created.

Parental Controls in practice

If you serve minors, implement parent linking and explicit consent. Default to no memory for teen accounts, allow opt-ins with clear scopes, and expose visibility settings and export options for guardians.

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