Amazon quietly removed requirements for human oversight from its internal AI policy templates, shifting responsibility to automated detection and enforcement tools. Critics warn that relying solely on automation could miss nuanced bias and safety issues, undermining effective model governance.

• Amazon removed human-in-the-loop requirements from internal AI policy templates, relying instead on automated detection tools like anomaly detectors and preset filters.
• Amazon told EU AI Act consultation its automated Risk Control Framework achieves 98%+ detection rates, based on in-house red-team testing.
• A test showed an AI tutor prompt to help a student cheat slipped past filters because it contained no explicit policy-violating terms, illustrating gaps in automated review.
• Critics warn automated-only moderation misses subtle bias and context-dependent risks, potentially allowing models to drift into unsafe territory like medical misinformation or coded extremist content.