{"id":"W3198590727","doi":"10.1177/20539517211039493","title":"Towards a United Nations Internal Regulation for Artificial Intelligence","year":2021,"lang":"en","type":"article","venue":"Big Data & Society","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Set (abstract data type); Work (physics); Commission; Artificial intelligence; Sociology; Symbolic artificial intelligence; Political science; Law; Computer science; Engineering; Artificial Intelligence System","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1051578,0.00155646,0.001683117,0.003818711,0.007450022,0.02233268,0.005154843,0.03184724,0.005777115],"category_scores_gemma":[0.1070848,0.001656164,0.003676577,0.002418158,0.01319233,0.01240102,0.009638543,0.03885412,0.005235853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008697938,"about_ca_system_score_gemma":0.03419616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01515101,"about_ca_topic_score_gemma":0.008779428,"domain_scores_codex":[0.898142,0.04060773,0.007762807,0.009150909,0.0359081,0.008428455],"domain_scores_gemma":[0.8720987,0.05893984,0.009741371,0.01822437,0.03673465,0.004261073],"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":[0.00001479202,0.00006457056,0.0003056045,0.00006423104,0.000008721008,0.00007784738,0.0009185684,0.0003286666,0.0003411602,0.9510332,0.03980221,0.007040287],"study_design_scores_gemma":[0.00002498113,0.00007233088,0.0009695349,0.001476221,0.0000302221,0.0001972026,0.0006530174,0.001074381,0.000886744,0.133765,0.8607194,0.0001310275],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.008880351,0.00635859,0.09534597,0.2366306,0.01401365,0.0007560124,0.0006296055,0.0009724867,0.6364127],"genre_scores_gemma":[0.1845434,0.005400352,0.2044649,0.379609,0.005433529,0.00553837,0.002157018,0.001327151,0.2115263],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1051578,"threshold_uncertainty_score":0.5561345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4157014412879985,"score_gpt":0.457841855578035,"score_spread":0.04214041429003657,"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."}}