{"id":"W4206734048","doi":"10.1109/mc.2021.3123796","title":"Assessing AI Fairness in Finance","year":2022,"lang":"en","type":"article","venue":"Computer","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"HSBC Bank USA","keywords":"Computer science; Management science; Economics","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":[0.04900539,0.0006119839,0.0009695187,0.003616039,0.00585249,0.008768829,0.001451823,0.00401927,0.004961591],"category_scores_gemma":[0.1785212,0.0002945788,0.0005244011,0.002464825,0.01817618,0.01006759,0.006115314,0.00481594,0.0004620492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007538171,"about_ca_system_score_gemma":0.005663572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008779769,"about_ca_topic_score_gemma":0.005408113,"domain_scores_codex":[0.948773,0.03509871,0.001471608,0.002825905,0.009171711,0.002659036],"domain_scores_gemma":[0.8873658,0.08001926,0.008855269,0.007305092,0.0124111,0.004043447],"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":[0.000133397,0.00008459538,0.01226373,0.00007434972,0.00006362156,0.00006310514,0.002174318,0.004196958,0.0001259061,0.9477597,0.003574059,0.02948616],"study_design_scores_gemma":[0.00002040142,0.00005971858,0.004346654,0.000082655,0.00001743408,0.0000415409,0.001745782,0.006938403,0.0002192845,0.9777651,0.008742865,0.0000203012],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2819745,0.005315264,0.1226315,0.09174693,0.001568469,0.0002942499,0.0001986895,0.0001197226,0.4961507],"genre_scores_gemma":[0.9879977,0.0003324014,0.007280377,0.001844539,0.0003433534,0.00007471421,0.00002414818,0.0000181002,0.002084814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04900539,"threshold_uncertainty_score":0.2591684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02093221990108481,"score_gpt":0.2433505631691631,"score_spread":0.2224183432680783,"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."}}