A new paper published on arXiv explores the concept of "societal relevance" as a framework for improving search engine and AI response quality. The research, building on prior work by Haider and Sundin, argues that traditional topical and user relevance metrics are insufficient for mitigating harmful content like misinformation and discrimination. The paper aims to define societal relevance, outline its application in search systems, and differentiate it from information quality measures, ultimately proposing a method for optimizing search outputs for the greater good. AI
IMPACT Introduces a new framework for developing more ethical and socially responsible AI and search systems.
RANK_REASON Academic paper published on arXiv discussing a new concept for AI and search. [lever_c_demoted from research: ic=1 ai=1.0]
Read on arXiv cs.IR (Information Retrieval) →
- AI Responses
- arXiv
- discrimination
- Haider
- information quality
- misinformation
- search engine
- Search systems and their features: What college students use to find and save information
- Societal Relevance Dimensions of Graduating in Political Science in Austria
- Sundin
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