{"id":"W3125403953","doi":"10.3386/w25619","title":"Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction","year":2019,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Impact of AI and Big Data on Business and Society","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Artificial intelligence; Computer science; Machine learning","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":[0.005461693,0.0004339729,0.0004271179,0.001078585,0.001270305,0.004497822,0.0007078393,0.002043612,0.01055914],"category_scores_gemma":[0.03865778,0.0002360807,0.0003524114,0.001221735,0.003610845,0.004656829,0.001524694,0.00316348,0.0009648118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001635395,"about_ca_system_score_gemma":0.001342795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003134663,"about_ca_topic_score_gemma":0.001699595,"domain_scores_codex":[0.9976991,0.001199047,0.00006659958,0.0002657449,0.0005880254,0.0001815511],"domain_scores_gemma":[0.9591311,0.03386539,0.002216647,0.001980534,0.001834384,0.000971872],"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":[0.001011751,0.0005747025,0.02964269,0.0003605091,0.0001182367,0.0005304221,0.001142262,0.02233142,0.002325865,0.732182,0.02975816,0.180022],"study_design_scores_gemma":[0.00009054021,0.00009545614,0.02599147,0.0001675657,0.00004129848,0.00009771143,0.0007773057,0.0311476,0.001003189,0.9277108,0.01283245,0.0000445159],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3974481,0.009630541,0.02813028,0.1904917,0.001343883,0.00008674234,0.000768643,0.0003191149,0.371781],"genre_scores_gemma":[0.9868922,0.001769768,0.002467082,0.003496649,0.0008820017,0.00002558762,0.00010832,0.00004591794,0.004312631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01055914,"threshold_uncertainty_score":0.03532386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5659333150523325,"score_gpt":0.5909869157845971,"score_spread":0.02505360073226459,"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."}}