山姆·奥特曼呼吁为人工智能建立「全球框架」，其构想类似于应用于AI领域的巴塞尔银行监管委员会。该框架旨在由各国自主执行标准，以平衡安全与科技进步，但国际监管的复杂性可能会面临如创新受阻等类似金融业的质疑。

巴塞尔模式的经验表明，繁重的监管往往有利于资金雄厚的大型企业，从而巩固现有巨头的地位。此外，要使全球联盟真正有效，必须纳入中国，否则可能会因地缘政治分歧而演变成科技领域的「铁幕」，进而让西方企业面临廉价竞争。

历史经验还揭示了全球监管的两大困境：一是专家在危机发生后才容易察觉问题，共同标准可能导致集体忽略特定漏洞；二是建立监管机制耗时漫长，而面对即将到来的强大AI系统，人类所剩的应对时间已非常有限。

Sam Altman calls for a "global framework" for AI, an idea resembling the Basel Committee on Banking Supervision applied to artificial intelligence. This framework suggests national enforcement of global standards to balance safety and progress, though international oversight faces compliance challenges similar to those in finance.

The Basel analogy suggests that onerous regulations tend to favor wealthy, established firms, thereby entrenching large tech giants. Furthermore, a truly effective global alliance must include China; otherwise, it risks creating a technological "iron curtain" that separates competing markets and impacts Western firms.

Historical experience also highlights two major regulatory challenges: first, experts often only identify systemic crises in hindsight, and shared standards may cause everyone to overlook identical vulnerabilities; second, establishing global agreements takes too long, whereas time to address imminent AI risks is extremely limited.