{"data":{"id":"23161927-17bf-435e-a732-69200d085d97","title":"A Deep Dive into Fairness, Bias, Threats, and Privacy in Recommender Systems: Insights and Future Research","summary":"This academic survey examines fairness, bias, threats, and privacy issues in recommender systems (AI systems that suggest products, content, or services to users). The paper analyzes insights from existing research and identifies areas needing future investigation, but does not present or evaluate specific technical fixes.","solution":"N/A -- no mitigation discussed in source.","labels":["research","safety"],"sourceUrl":"https://dl.acm.org/doi/abs/10.1145/3821405?af=R","publishedAt":"2026-07-11T12:01:13.524Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["safety"],"aiComponentTargeted":null,"llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}