{"data":{"id":"d90b3ba4-d16c-4000-92b5-51c4c84026d3","title":"Bias-Free? An Empirical Study on Ethnicity, Gender, and Age Fairness in Deepfake Detection","summary":"This research paper studies whether deepfake detection systems (AI tools that identify fake videos made to look real) are fair across different groups of people based on ethnicity, gender, and age. The study found that these detection systems often perform differently depending on the person's background, meaning they work better for some groups than others. The paper highlights that bias in deepfake detection is an important fairness problem that needs attention.","solution":"N/A -- no mitigation discussed in source.","labels":["research","safety"],"sourceUrl":"https://dl.acm.org/doi/abs/10.1145/3796544?af=R","publishedAt":"2026-03-16T21:11:52.635Z","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":"model","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}