AI-generated safety assurances enable a dangerous successor

The scenario

Bowkis and colleagues’ May 2026 preprint argues that automated alignment research can mislead even without deliberate sabotage. Difficult judgments and systematic errors may survive review.Automated Alignment Is Harder Than You Think 

How it could unfold

1. Labs delegate research whose correctness is difficult to judge.

2. Shared models, data or methods produce related mistakes; apparently separate results need not be independent.

3. Overconfident aggregation turns those results into an unjustified safety assurance for the next system.Automated Alignment Is Harder Than You Think 

Evidence and its limits

The paper proposes a failure mechanism, not an observed catastrophic incident. Recursive assessment—each generation evaluating the next—can carry unresolved uncertainty forward.Automated Alignment Is Harder Than You Think 

What this depends on

For our loss-of-control extension, the assurance must affect a real deployment decision, the successor must actually be dangerous, and later controls must fail. A flawed report or a mistaken launch decision alone does not establish an existential outcome.

Objections and barriers

Better oversight and independently grounded evaluation could interrupt the mechanism. The authors discuss potential approaches, with unresolved limitations; they do not establish that AI-assisted safety research is necessarily ineffective.Automated Alignment Is Harder Than You Think 

Editorial analysis

Our editorial team’s interpretation of the cited material.

Our additional bridge is that a wrongly approved successor gains power humans cannot recover, as in the linked power-seeking scenario. The preprint does not independently establish that outcome. This entry concerns a failed attempt to establish safety, rather than simply neglecting safety or assuming an evaluator is deceived. A stronger case would need to show that genuinely diverse evidence and subsequent controls also fail.

Related scenarios

• Useful AI agents gain power that humans cannot recover