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AI safety prizes: A pull funding model for uncertain research

By PulseAugur Editorial · [1 sources] ·

The concept of AI safety prizes is explored as an alternative to traditional upfront funding for research. This 'pull funding' model, where rewards are given after valuable progress is made, is particularly effective when the path to a solution is unclear and the outcome is verifiable. While prizes can incentivize innovation and attract diverse talent, as seen in DARPA's autonomous vehicle challenges, they also carry risks such as distorting research incentives and discouraging collaboration. AI philanthropists might find prizes appealing due to potential high investment returns and the future availability of AI labor for evaluation. AI

IMPACT This funding model could reshape how AI safety research is incentivized and executed, potentially accelerating progress in unpredictable areas.

RANK_REASON The item discusses the concept and mechanics of AI safety prizes as a funding mechanism, rather than announcing a specific event or release.

Read on LessWrong (AI tag) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI safety prizes: A pull funding model for uncertain research

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The item discusses the concept and mechanics of AI safety prizes as a funding mechanism, rather than announcing a specific event or release.
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High
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57 days old
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COVERAGE [1]

  1. LessWrong (AI tag) TIER_1 English(EN) · Oscar ·

    AI safety prizes

    <p><span>Rather than paying up front for AI safety research (push funding), perhaps we should pay after the fact for the work that made the most progress (pull funding). This way, you only pay for work that was actually valuable.</span><span class="footnote-reference" id="fnrefis…

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