{"id":"W4400071125","doi":"10.2139/ssrn.4874061","title":"Employer and Employee Responses to Generative AI: Early Evidence","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Generative grammar; Psychology; Business; Computer science; Artificial intelligence","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":[0.01734976,0.0002494912,0.0002566017,0.00112397,0.002352208,0.00471419,0.001114762,0.004173977,0.01457912],"category_scores_gemma":[0.1118554,0.0002995264,0.0002865302,0.0009073297,0.00446926,0.002195314,0.002631312,0.003973139,0.001053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001671342,"about_ca_system_score_gemma":0.00220238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002828091,"about_ca_topic_score_gemma":0.003165475,"domain_scores_codex":[0.9826406,0.01244773,0.0005364224,0.0005898874,0.002306032,0.001479416],"domain_scores_gemma":[0.6823619,0.2765169,0.02155239,0.00718203,0.00746279,0.004923978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003253658,0.006576009,0.5394063,0.001406122,0.0003991621,0.001472457,0.115922,0.00153963,0.001786405,0.1041673,0.007060145,0.217011],"study_design_scores_gemma":[0.000422589,0.001386709,0.6216034,0.002420444,0.0002514134,0.0009865747,0.1807547,0.002845756,0.003251211,0.1245384,0.06140438,0.0001345443],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8802423,0.002491579,0.001926207,0.01837595,0.0001808294,0.00009102043,0.00007900695,0.00001682755,0.09659639],"genre_scores_gemma":[0.9949147,0.0007891872,0.0002213951,0.001949754,0.0001108473,0.00003968297,0.00003171213,0.000007709185,0.001934982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01734976,"threshold_uncertainty_score":0.09175545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05339062990847071,"score_gpt":0.4067284234681656,"score_spread":0.3533377935596949,"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."}}