A survey of 112 papers on agentic AI for social good reveals a significant gap in specifying geographic context, particularly for goals related to institutions and policy. Researchers found that while AI systems are proposed for global benefits like the UN's Sustainable Development Goals, they often lack accountability to the communities they aim to serve. The study also noted that only a quarter of the papers reported any real-world deployment or testing, highlighting several accountability issues and proposing a standard for more context-specific and participatory AI development. AI
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IMPACT Highlights critical gaps in accountability and geographic specificity for AI systems intended for social good, urging more participatory development.
RANK_REASON The cluster contains an academic paper detailing research findings on agentic AI for social good. [lever_c_demoted from research: ic=1 ai=1.0]