{"id":"W4366760640","doi":"10.2139/ssrn.4414212","title":"The Governance of Artificial Intelligence in Canada: Findings and Opportunities from a Review of 84 AI Governance Initiatives","year":2023,"lang":"en","type":"review","venue":"SSRN Electronic Journal","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Toronto","funders":"","keywords":"Corporate governance; Variety (cybernetics); Political science; Workforce; Public relations; State (computer science); Public administration; Business; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.006044294,0.0002229345,0.001154275,0.00003612998,0.0003894595,0.0000685055,0.0007307736,0.0001700124,0.00001918654],"category_scores_gemma":[0.003301952,0.0001664597,0.0002131783,0.0004245429,0.0005339232,0.0002869477,0.0000839421,0.002637737,0.0000011116],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002483206,"about_ca_system_score_gemma":0.06501208,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6820118,"about_ca_topic_score_gemma":0.978116,"domain_scores_codex":[0.9959252,0.0006861067,0.00113847,0.0001908724,0.0008514295,0.001207907],"domain_scores_gemma":[0.9961993,0.001787245,0.001481189,0.000150448,0.0002866437,0.00009514356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002917198,0.000006346348,0.000004863819,0.001806311,0.00009565808,0.000004265621,0.0006297695,7.47528e-8,2.125613e-8,0.4879799,0.0000892823,0.5093806],"study_design_scores_gemma":[0.0000488827,0.00009609175,0.0000690042,0.109054,0.0002752817,0.000008200536,0.01260599,0.000002431749,7.395237e-7,0.3749608,0.5024908,0.0003878247],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000447865,0.9933152,0.00001428219,0.005200368,0.0002372121,0.0002852568,0.0001354844,0.000003945876,0.0007634938],"genre_scores_gemma":[0.001202032,0.9981659,0.000004512455,0.0001848539,0.0001860379,0.000009276692,0.000003839345,0.00002215817,0.000221374],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5089927,"threshold_uncertainty_score":0.9996632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1155874039689404,"score_gpt":0.3911734161911577,"score_spread":0.2755860122222173,"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."}}