{"id":"W4402061313","doi":"10.1017/dap.2024.26","title":"Toward a trustworthy and inclusive data governance policy for the use of artificial intelligence in Africa","year":2024,"lang":"en","type":"article","venue":"Data & Policy","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto; Artificial Intelligence in Medicine (Canada); York University","funders":"","keywords":"Trustworthiness; Corporate governance; Political science; Artificial intelligence; Computer science; Public relations; Psychology; Data science; Computer security; Business; Sociology","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":[0.05890501,0.0004261412,0.0006177315,0.00344513,0.006000415,0.01720054,0.001979435,0.005355683,0.002820117],"category_scores_gemma":[0.06814574,0.0007472379,0.00071393,0.002888952,0.0101904,0.02119935,0.014829,0.007154608,0.0005707304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009356677,"about_ca_system_score_gemma":0.03758479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01116201,"about_ca_topic_score_gemma":0.00673635,"domain_scores_codex":[0.9611979,0.02296217,0.00250985,0.002295154,0.006324164,0.004710776],"domain_scores_gemma":[0.9494407,0.02304441,0.007330358,0.005620426,0.01060559,0.003958502],"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":[0.00003082051,0.00005198563,0.002353202,0.0001110942,0.00001788123,0.0001702319,0.003226677,0.002461721,0.0004970901,0.9659638,0.008570055,0.01654561],"study_design_scores_gemma":[0.00009495008,0.0001038347,0.00309218,0.002046073,0.00004570973,0.0002837607,0.009349321,0.01044783,0.00302515,0.5904971,0.3809067,0.0001073279],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09580532,0.002862337,0.2328309,0.478806,0.001072108,0.001114744,0.0003666428,0.0002676077,0.1868744],"genre_scores_gemma":[0.8609712,0.002230261,0.08344424,0.03261422,0.0005346742,0.00102794,0.0001900697,0.00009699193,0.01889055],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05890501,"threshold_uncertainty_score":0.3115233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2050639551131102,"score_gpt":0.3442383288027966,"score_spread":0.1391743736896864,"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."}}