{"id":"W4293318788","doi":"10.29173/irie484","title":"Ethics for Nerds","year":2022,"lang":"en","type":"article","venue":"The International Review of Information Ethics","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Volkswagen Foundation; Deutsche Forschungsgemeinschaft","keywords":"Computer ethics; Engineering ethics; Informatics; Information ethics; Economic Justice; Computer science; Public relations; Engineering management; Sociology; Political science; Engineering; Law; Meta-ethics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01991169,0.0003622615,0.0004396541,0.0006902323,0.00418844,0.006784869,0.0008986241,0.005970578,0.006975416],"category_scores_gemma":[0.04482125,0.0002225288,0.0004405385,0.0005712052,0.01317652,0.006864018,0.004910368,0.00665343,0.002358416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005357024,"about_ca_system_score_gemma":0.01651569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002867314,"about_ca_topic_score_gemma":0.002943116,"domain_scores_codex":[0.9633026,0.0253695,0.001680793,0.0024441,0.005964449,0.001238593],"domain_scores_gemma":[0.9726944,0.01408424,0.001931905,0.004306067,0.004405396,0.002577957],"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":[0.00001034785,0.00003474452,0.0009796178,0.0002144051,0.00001056731,0.0002153082,0.01225982,0.0001691199,0.0002355414,0.7655296,0.1574004,0.06294059],"study_design_scores_gemma":[0.000002490935,0.00001202637,0.0004410813,0.0004857182,0.00000231851,0.0002196797,0.002432148,0.00006109751,0.0001065378,0.05453523,0.941694,0.000007702416],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0140943,0.02597461,0.01857859,0.539804,0.007273491,0.0001403835,0.0001342854,0.0002433972,0.393757],"genre_scores_gemma":[0.5398877,0.02443079,0.02335174,0.2022467,0.004045438,0.0004231181,0.0002975848,0.0003501883,0.2049668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9958116,"threshold_uncertainty_score":0.1053044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1531069155345786,"score_gpt":0.4808356990554108,"score_spread":0.3277287835208322,"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."}}