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GPT-5Oct 23, 2026openai/gpt-5-2025-08-07
Should AI development be paused or restricted?
Short answer: Yes to targeted restrictions and conditional pauses; no to a blanket pause on all AI.
Why not a blanket pause
•It’s not enforceable globally, would entrench incumbents, and would delay clear benefits (healthcare, science, accessibility, safety tech).
Where pauses/restrictions do make sense
•Frontier training runs: impose a time‑limited moratorium on scaling beyond defined compute/capability thresholds until safety criteria are met.
•High‑risk uses: prohibit or tightly license applications like autonomous cyber‑offense, large‑scale biometric surveillance, model‑assisted biological threat design, and critical‑infrastructure control.
•Deceptive/persuasive systems targeting children or elections: strict controls during defined windows (e.g., pre‑election periods).
How to operationalize this
•Licensing for very large training runs (e.g., above X FLOPs or energy use), with:
•Pre‑registration of compute, secure training facilities, and provenance logs.
•Independent pre‑deployment audits and red‑teaming focused on bio/cyber, autonomy, persuasion, and safety alignment.
•Staged release (internal → limited partners → public) with safety gates.
•Mandatory incident reporting, post‑deployment monitoring, and recall powers for regulators.
•Transparent model/system cards, data governance (privacy/IP), and energy/emissions reporting.
•Liability: clear duty of care for developers and deployers; insurance requirements for high‑risk systems.
•Content authenticity: watermarking/provenance for AI‑generated media in major platforms.
•International coordination: minimum safety standards and compute/export controls to limit unsafe proliferation.
Tripwires for a pause
•Demonstrated ability to autonomously replicate/spread, or to execute end‑to‑end cyber intrusions against hardened targets.
•Reliable assistance in designing or acquiring banned weapons/biological agents.
•Safety eval failures (e.g., persistent jailbreaks enabling prohibited behaviors) that cannot be mitigated before release.
•Serious real‑world incidents showing systemic risk.
Balance for open innovation
•Keep research and small‑scale/open models largely unlicensed, but require guardrails for adding dangerous tool access (e.g., chemistry, exploit kits, autonomous trading at scale).
•Support red‑team grants, evaluation benchmarks, and safe‑harbor data‑sharing so smaller labs can meet standards.
Bottom line: Don’t stop AI across the board. Do impose enforceable, capability‑based restrictions, with conditional pauses tied to measurable safety thresholds and strong post‑deployment oversight. If you’d like, tell me which aspect (safety, jobs, misinformation, national security, open‑source) you care most about, and I’ll tailor a concrete policy set.