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AI learns optimal information disclosure for human decision-making

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a method for selective information disclosure to human decision-makers, aiming to optimize outcomes under budget constraints. The proposed policy learns when to reveal supporting information, outperforming both no disclosure and full disclosure in experiments. User studies indicated that AI-led disclosure can improve human-AI team performance, though this advantage may vary by task and how information is presented. AI

IMPACT This research could lead to more effective human-AI collaboration by optimizing information flow in critical decision-making scenarios.

RANK_REASON Research paper on selective information disclosure in AI-human decision-making. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

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

AI learns optimal information disclosure for human decision-making

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Research paper on selective information disclosure in AI-human decision-making. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Carlotta Giacchetta, Alessando Bogani, Cesare Barbera, Giovanni De Toni, Michele Caprio, Andrea Pugnana, Andrea Passerini ·

    Should I stay or should I show? Learning to selectively disclose information

    arXiv:2609.39818v1 Announce Type: new Abstract: In many high-stakes settings, human decision-makers can acquire support information before making a decision. However, acquiring information is costly, and disclosure may fail to improve human decisions or may even impair them. We t…

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