{"id":"W4398133596","doi":"10.1126/science.adn0117","title":"Managing extreme AI risks amid rapid progress","year":2024,"lang":"en","type":"article","venue":"Science","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":266,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Toronto; Schwartz/Reisman Emergency Medicine Institute; Vector Institute; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Risk analysis (engineering); Corporate governance; Computer science; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.004015537,0.00007963698,0.00008433443,0.0001545871,0.00167897,0.001837836,0.0006655824,0.00006947695,0.0001703205],"category_scores_gemma":[0.0005296886,0.00007102192,0.00004402588,0.001470278,0.003444129,0.001515415,0.0001043637,0.0002966788,0.0001504376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001483452,"about_ca_system_score_gemma":0.0009994216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008490217,"about_ca_topic_score_gemma":0.0004093731,"domain_scores_codex":[0.9978969,0.00007399719,0.0001165878,0.0003456607,0.0009913814,0.0005754639],"domain_scores_gemma":[0.999255,0.00009989987,0.00002632298,0.0001660327,0.000216758,0.000235961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002480133,0.00002887705,0.001086837,0.00003213332,0.000008752085,0.00004804543,0.04896864,0.000005838368,0.0009167519,0.5889792,0.002501072,0.3574213],"study_design_scores_gemma":[0.0001086009,0.0001024425,0.007171359,0.0002640605,0.00002152135,0.000002458268,0.01024722,0.002204404,0.0007628596,0.4068099,0.5717917,0.0005134759],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1066209,0.008636965,0.000749135,0.2376187,0.006158955,0.0005784099,0.000008457274,0.001031816,0.6385966],"genre_scores_gemma":[0.9957356,0.0005157533,0.0003042654,0.0009818609,0.0003969916,0.000006029786,3.006414e-7,0.000007640316,0.002051598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8891146,"threshold_uncertainty_score":0.9996207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1522338606013797,"score_gpt":0.45875427720543,"score_spread":0.3065204166040503,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}