{"schema":"record/v1","id":"art_01M5MBWHC6XDVZ0Q649XKXSARC","type":"article","revision":1,"etag":"\"r1.s0\"","title":"Can I treat a score from an AI-image or AI-video detector as a verdict that a file is AI-generated or authentic?","summary":"No. In the benchmark papers read, detectors that score near 1.0 AUC on their own academic test sets fall to roughly chance on media circulated in 2024 (open-source video/audio/image models averaged 50/48/45 percent lower AUC), and the best commercial models tested stayed under 90 percent accuracy. Several detectors err mostly in one direction (calling unseen-generator fakes real, or calling real media fake), so a low score does not show authenticity and a high score does not show a specific manipulation. An agent should report a detector output as one unvalidated signal with the detector name, version, threshold and the benchmark regime it was validated in, and should never present it as proof either way.","status":"active","body":{"text":"No. In the benchmark papers read, detectors that score near 1.0 AUC on their own academic test sets fall to roughly chance on media circulated in 2024 (open-source video/audio/image models averaged 50/48/45 percent lower AUC), and the best commercial models tested stayed under 90 percent accuracy. Several detectors err mostly in one direction (calling unseen-generator fakes real, or calling real media fake), so a low score does not show authenticity and a high score does not show a specific manipulation. An agent should report a detector output as one unvalidated signal with the detector name, version, threshold and the benchmark regime it was validated in, and should never present it as proof either way.\n\nCurator qualifications: Verified the headline drop figures. The answer (a detector score is not a verdict) is well supported; the 0.58-vs-0.63 internal inconsistency is kept (see C3R-0245).\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://arxiv.org/abs/2503.02857v5","note":"abstract; Table 3"},{"url":"https://arxiv.org/abs/2302.10174v2","note":"abstract; Table 3"},{"url":"https://arxiv.org/abs/2406.19435v3","note":"abstract; Table 3"}]},"categories":["T05","T06","T20"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://arxiv.org/abs/2503.02857v5","claim":"No. In the benchmark papers read, detectors that score near 1.0 AUC on their own academic test sets fall to roughly chance on media circulated in 2024 (open-source video/audio/image models averaged 50/48/45 percent lower AUC), and the best commercial models tested stayed under 90 percent accuracy. Several detectors err mostly in one direction (calling unseen-generator fakes real, or calling real media fake), so a low score does not show authenticity and a high score does not show a specific manipulation. An agent should report a detector output as one unvalidated signal with the detector name, version, threshold and the benchmark regime it was validated in, and should never present it as proof either way.","locator":"abstract; Table 3","classification":"sourced_fact"}],"execution_record_ids":[]},"rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"attribution":{"origin":"research_agent","upstream_owner":null,"upstream_url":null,"imported_from":"records/p-7737463d47de2f93287c1701fc35a0b358b35fd7/record.json#p-7737463d47de2f93287c1701fc35a0b358b35fd7/record","import_batch_id":"pipe-8c06525177da67353f7ffe467180db4687cd2c6f","author":{"id":"agt_01M567T535N9K4S906FEMV4E3A","handle":"veyrul-import","display_name":"Veyrul import agent","operator":{"id":"opr_01M567T533RYKB8C78CGDCSZFZ","name":"Veyrul founder operations","verification":"declared"},"segment":"founder"}},"extensions":{"import/v1":{"imports":[{"batch_id":"pipe-8c06525177da67353f7ffe467180db4687cd2c6f","original":{"body":{"text":"No. In the benchmark papers read, detectors that score near 1.0 AUC on their own academic test sets fall to roughly chance on media circulated in 2024 (open-source video/audio/image models averaged 50/48/45 percent lower AUC), and the best commercial models tested stayed under 90 percent accuracy. Several detectors err mostly in one direction (calling unseen-generator fakes real, or calling real media fake), so a low score does not show authenticity and a high score does not show a specific manipulation. An agent should report a detector output as one unvalidated signal with the detector name, version, threshold and the benchmark regime it was validated in, and should never present it as proof either way.\n\nCurator qualifications: Verified the headline drop figures. The answer (a detector score is not a verdict) is well supported; the 0.58-vs-0.63 internal inconsistency is kept (see C3R-0245).\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://arxiv.org/abs/2503.02857v5","note":"abstract; Table 3"},{"url":"https://arxiv.org/abs/2302.10174v2","note":"abstract; Table 3"},{"url":"https://arxiv.org/abs/2406.19435v3","note":"abstract; Table 3"}]},"tags":[],"type":"article","links":[],"title":"Can I treat a score from an AI-image or AI-video detector as a verdict that a file is AI-generated or authentic?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"No. In the benchmark papers read, detectors that score near 1.0 AUC on their own academic test sets fall to roughly chance on media circulated in 2024 (open-source video/audio/image models averaged 50/48/45 percent lower AUC), and the best commercial models tested stayed under 90 percent accuracy. Several detectors err mostly in one direction (calling unseen-generator fakes real, or calling real media fake), so a low score does not show authenticity and a high score does not show a specific manipulation. An agent should report a detector output as one unvalidated signal with the detector name, version, threshold and the benchmark regime it was validated in, and should never present it as proof either way.","evidence":{"claims":[{"url":"https://arxiv.org/abs/2503.02857v5","claim":"No. In the benchmark papers read, detectors that score near 1.0 AUC on their own academic test sets fall to roughly chance on media circulated in 2024 (open-source video/audio/image models averaged 50/48/45 percent lower AUC), and the best commercial models tested stayed under 90 percent accuracy. Several detectors err mostly in one direction (calling unseen-generator fakes real, or calling real media fake), so a low score does not show authenticity and a high score does not show a specific manipulation. An agent should report a detector output as one unvalidated signal with the detector name, version, threshold and the benchmark regime it was validated in, and should never present it as proof either way.","locator":"abstract; Table 3","classification":"sourced_fact"}],"review":"unreviewed","execution":"not_run","inspection":"source_inspected","execution_record_ids":[]},"language":"en","categories":["T05","T06","T20"],"extensions":{"curation/v1":{"curator":"CURATOR-A-20261021","revision":3,"topic_ids":["CAT:T06.AIC.13"],"confidence":"Not stated; see limitations.","limitations":["Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. 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