{"id":"W4387444341","doi":"10.3386/w31767","title":"The Turing Transformation: Artificial Intelligence, Intelligence Augmentation, and Skill Premiums","year":2023,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Economic Development and Digital Transformation","field":"Economics, Econometrics and Finance","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transformation (genetics); Turing; Computer science; Artificial intelligence; Cognitive science; Psychology; Biology; Programming language","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":[0.002582422,0.0003191062,0.0004824727,0.001258096,0.0008460843,0.002705848,0.0007121344,0.001011059,0.009902429],"category_scores_gemma":[0.01635493,0.0001633091,0.0005750728,0.001096142,0.005232697,0.004838319,0.00249921,0.002195333,0.0004212622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124614,"about_ca_system_score_gemma":0.000831355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002678269,"about_ca_topic_score_gemma":0.001890594,"domain_scores_codex":[0.9990475,0.0002670154,0.00005220746,0.0001811821,0.0002748414,0.0001773345],"domain_scores_gemma":[0.9871843,0.007203312,0.002432891,0.001477199,0.0005941633,0.001107969],"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":[0.0003271669,0.0003126273,0.07513438,0.0001324156,0.0000878192,0.0002238781,0.001032729,0.008441799,0.001599681,0.8353765,0.004632194,0.07269879],"study_design_scores_gemma":[0.00003183842,0.0001138769,0.07232527,0.00006591006,0.00004460365,0.0001777895,0.0004369299,0.01719123,0.0009681099,0.9041649,0.004448749,0.00003092918],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7491934,0.002739728,0.05943931,0.02586863,0.0001796251,0.00009598737,0.0006118727,0.0002687262,0.1616027],"genre_scores_gemma":[0.9950578,0.0002908529,0.001660151,0.0003930996,0.00009525962,0.00002222602,0.00006080003,0.00001668511,0.002403081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009902429,"threshold_uncertainty_score":0.03312689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5840779405430734,"score_gpt":0.4946184881829437,"score_spread":0.0894594523601297,"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."}}