{"id":"W3184694980","doi":"10.1287/mksc.2021.1295","title":"Frontiers: Can an Artificial Intelligence Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb","year":2021,"lang":"en","type":"article","venue":"Marketing Science","topic":"Sharing Economy and Platforms","field":"Business, Management and Accounting","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Revenue; Context (archaeology); Algorithm; Population; Computer science; Economics; Machine learning; Finance; Geography; 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":[0.003387337,0.000303626,0.0005653158,0.0004810895,0.0008108183,0.001741177,0.0007147204,0.0007788505,0.00452336],"category_scores_gemma":[0.02224532,0.0001033794,0.0004083416,0.0005771366,0.001446283,0.002490116,0.001419885,0.00122455,0.00027967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061002,"about_ca_system_score_gemma":0.0009764038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005306262,"about_ca_topic_score_gemma":0.003122256,"domain_scores_codex":[0.9980547,0.001231852,0.00003637669,0.0001733187,0.0002144074,0.0002892492],"domain_scores_gemma":[0.9888974,0.007184925,0.001934588,0.0009221246,0.0005646856,0.000496301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003880501,0.004990894,0.4088588,0.0005721521,0.0004385533,0.0006591632,0.002851842,0.1363337,0.006603628,0.1884665,0.008649591,0.2376946],"study_design_scores_gemma":[0.0006244073,0.003989442,0.3220039,0.0001914731,0.00037109,0.0002373867,0.005465752,0.5473893,0.005676311,0.09234834,0.02162782,0.00007475895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9761671,0.0003071905,0.009914883,0.002249983,0.00004793372,0.00008151109,0.0001121112,0.00005027029,0.01106903],"genre_scores_gemma":[0.9976454,0.0000660021,0.001522329,0.0001558737,0.00002263752,0.00002827759,0.00003817159,0.000005707935,0.0005156476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005306262,"threshold_uncertainty_score":0.01791412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02925166095697394,"score_gpt":0.2638301363844498,"score_spread":0.2345784754274759,"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."}}