{"id":"W4285606202","doi":"10.24963/ijcai.2022/811","title":"Ethics and Governance of Artificial Intelligence: A Survey of Machine Learning Researchers (Extended Abstract)","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute on Governance","funders":"University of Oxford; Open Philanthropy Project; Georgetown University; Canadian Institute for Advanced Research","keywords":"Relevance (law); Corporate governance; Artificial intelligence; Work (physics); Political science; Public relations; Public sector; Private sector; Computer science; Engineering; Management; Law; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01110883,0.0002260675,0.000439977,0.0002026776,0.001245247,0.0001799666,0.001550862,0.0002148021,0.0007351761],"category_scores_gemma":[0.02207312,0.0002068199,0.0001763592,0.0007940421,0.002016574,0.0003674703,0.0006768326,0.002429262,0.000006063491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002317712,"about_ca_system_score_gemma":0.0007280247,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01897662,"about_ca_topic_score_gemma":0.005576087,"domain_scores_codex":[0.9951543,0.0003205549,0.00114294,0.0004389246,0.002532186,0.0004111553],"domain_scores_gemma":[0.9931941,0.00164183,0.001402049,0.0001664681,0.003445642,0.0001499249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004924646,0.0003677036,0.001817077,0.00007910432,0.00007467921,9.177916e-7,0.03154921,0.0004256354,0.004904335,0.9435599,0.00004289865,0.01668604],"study_design_scores_gemma":[0.00009940377,0.001064147,0.02079252,0.0008011992,0.00005230007,0.000004567552,0.07063801,0.01757922,0.1103986,0.7765636,0.001295868,0.0007105704],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8867783,0.0002625291,0.0005846254,0.06315984,0.001824499,0.001221587,0.000497505,0.00008576691,0.04558537],"genre_scores_gemma":[0.9980321,0.001101104,0.0002480062,0.0001413266,0.00008492994,0.00001982335,0.000006083142,0.00002089857,0.0003457554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1669963,"threshold_uncertainty_score":0.9998721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2634526621512286,"score_gpt":0.41029010875163,"score_spread":0.1468374466004014,"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."}}