DeepMind's "Frontier Safety Framework" is weak and unambitious
By Zach Stein-Perlman @ 2024-05-18T03:00 (+54)
This is a crosspost, probably from LessWrong. Try viewing it there.
nullSummaryBot @ 2024-05-20T20:29 (+1)
Executive summary: DeepMind's "Frontier Safety Framework" for AI development is a step in the right direction but lacks ambition, specificity, and firm commitments compared to other labs' responsible scaling plans.
Key points:
- The Frontier Safety Framework (FSF) involves evaluating models for dangerous capabilities at regular intervals, but the details are vague and not committed to.
- The FSF discusses potential security and deployment mitigations based on risk assessments, but does not specify triggers or make advance commitments.
- DeepMind's security practices seem behind other labs, e.g. allowing unilateral access to model weights at most levels.
- The FSF's capability thresholds for concern ("Critical Capability Levels") seem quite high.
- Compared to Anthropic, OpenAI, and Microsoft's responsible scaling plans, DeepMind's FSF is less ambitious, specific, and committed to. Meta has no public plan.
- The FSF may have been rushed out and the DeepMind safety team likely has better, more detailed (but unpublished) plans.
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