AI companies are unlikely to make high-assurance safety cases if timelines are short

Executive summary: AI companies are unlikely to produce high-assurance safety cases for preventing existential risks in short timelines due to technical, logistical, and competitive challenges, raising concerns about their ability to mitigate risks effectively.

Key points:

1. High-assurance safety cases require auditable arguments that AI systems have minimal existential risk, but no current framework guarantees this commitment.
2. Achieving necessary security (e.g., SL5 level) and mitigating risks like scheming and misalignment are technically and operationally difficult within a 4-year timeline.
3. AI companies are unlikely (<20%) to succeed in making safety cases before deploying Top-human-Expert-Dominating AI (TEDAI) and unlikely to pause development without external pressure.
4. Accelerating safety work using pre-TEDAI AI systems appears insufficient due to integration delays and the difficulty of ensuring these systems are free of sabotage.
5. Current government and inter-company coordination efforts are inadequate to enforce safety case commitments, especially under competitive pressures.
6. Work on safety cases for less stringent risk thresholds (e.g., 1% or 5%) might be more feasible but still faces significant challenges and limited impact on behavior.

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