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Shared Discovery Paradox: Pooling Info Can Harm Search Outcomes

By PulseAugur Editorial · [1 sources] ·

A new benchmark, the "Shared Discovery Paradox," analyzes how pooling dispersed information into a single recommendation can paradoxically lead to worse search outcomes. While consolidating information improves the accuracy of the best single recommendation, it significantly reduces overall group discovery when agents repeatedly act on this single pooled view. The study proposes that this is a protocol failure, not an information failure, suggesting that a "one-answer rule" compresses a portfolio of actions into a single, repeated choice. The research also explores scenarios with self-interested searchers and introduces a "sole-rescue reward" to incentivize better outcomes. AI

IMPACT Highlights potential pitfalls in how AI systems aggregate and present information, suggesting protocol design is crucial for effective decision-making.

RANK_REASON Academic paper analyzing a novel paradox in information sharing and search protocols. [lever_c_demoted from research: ic=1 ai=0.7]

Read on Hugging Face Daily Papers →

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

Shared Discovery Paradox: Pooling Info Can Harm Search Outcomes

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Academic paper analyzing a novel paradox in information sharing and search protocols. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    The Shared Discovery Paradox: How a One-Answer Rule Turns Better Information into Worse Search

    Organizations often pool dispersed information into one ranking and then allow many agents to act on that shared view. In a discovery problem, this can improve beliefs while reducing coverage. We develop an exactly solvable benchmark with sixteen boxes, one target, eight searcher…

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