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Safety and alignment

OpenAI details deployed Rule-Based Rewards safeguards

OpenAI published Rule-Based Rewards, a safety-training method used since GPT-4 and in GPT-4o mini that matched human-feedback safety performance while reducing over-refusals and the need for repeated human labeling.

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CURRENT ASSESSMENT · REVISION 1
AWAY FROM DOOM48confidence 96/100

Why it moved the index

The method was already deployed in public frontier models and provided an updateable, measurable control for harmful behavior, strengthening safeguards beyond a laboratory-only result.

Assessment history

  1. R1
    Away 48 · confidence 96

    New July 2024 research publication paired with verified deployment in public models.

    12 Aug 2026

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  1. DoomBench assesses “OpenAI details deployed Rule-Based Rewards safeguards” as evidence moving away from doom, with magnitude 48 and confidence 96 out of 100 in the safety and alignment category.

  2. The DoomBench assessment of “OpenAI details deployed Rule-Based Rewards safeguards” is based on reporting from OpenAI and records the editorial rationale, source quality, attribution, and revision history.

  3. DoomBench summarizes “OpenAI details deployed Rule-Based Rewards safeguards” as follows: OpenAI published Rule-Based Rewards, a safety-training method used since GPT-4 and in GPT-4o mini that matched human-feedback safety performance...

    https://www.doombench.com/news/openai-details-deployed-rule-based-rewards-safeguards-2024-07-24