{"id":"W4415257531","doi":"10.1145/3757397","title":"AI Ethics and Social Norms: Exploring ChatGPT's Capabilities From What to How","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transparency (behavior); Research ethics; Context (archaeology); Information ethics; Everyday life; Social responsibility; Empirical research; Data collection","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":[0.04052729,0.0003360421,0.0003602547,0.002412794,0.004071371,0.007199863,0.001423908,0.001364885,0.001506119],"category_scores_gemma":[0.1726292,0.000403536,0.0002834406,0.001148006,0.0136037,0.009479913,0.007183486,0.002304323,0.0002744547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003255793,"about_ca_system_score_gemma":0.003704656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002284565,"about_ca_topic_score_gemma":0.00327659,"domain_scores_codex":[0.9324726,0.05879962,0.001547358,0.00197308,0.004120098,0.001087307],"domain_scores_gemma":[0.7441734,0.2111109,0.01468106,0.01302205,0.01166006,0.005352358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001767147,0.0001444189,0.05472504,0.0004158474,0.00003955709,0.0007070521,0.8293757,0.000566392,0.003415017,0.03670819,0.001040681,0.07268542],"study_design_scores_gemma":[0.00007383699,0.0005664105,0.06744712,0.001288469,0.00009271794,0.002466016,0.7226179,0.01875683,0.007569807,0.1133046,0.06558103,0.0002351941],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9081971,0.0004591521,0.04883318,0.006528484,0.00008204406,0.0002807589,0.00008086627,0.0003118838,0.03522649],"genre_scores_gemma":[0.9935077,0.00007955363,0.005404142,0.0002376811,0.00001855592,0.0001184999,0.00001900125,0.00003290713,0.0005818567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04052729,"threshold_uncertainty_score":0.2143314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1778373734369819,"score_gpt":0.4175649082818309,"score_spread":0.239727534844849,"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."}}