{"id":"W4321276891","doi":"10.1145/3544549.3583178","title":"Human-Centered Responsible Artificial Intelligence: Current & Future Trends","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsoft (Canada); Nokia (Canada); Bell (Canada)","funders":"","keywords":"Terminology; Humanity; Engineering ethics; Work (physics); Computer science; Research ethics; Data science; Knowledge management; Management science; Political science; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003363145,0.0003659198,0.0004997404,0.0004879472,0.001569662,0.001117166,0.001090706,0.001178002,0.002208838],"category_scores_gemma":[0.0008624094,0.0003618015,0.0004570813,0.0007281353,0.0005702319,0.000191881,0.0008156303,0.002350015,0.0006711025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000330841,"about_ca_system_score_gemma":0.00138587,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007355174,"about_ca_topic_score_gemma":0.1089573,"domain_scores_codex":[0.9959155,0.0006693627,0.0006652845,0.0007376394,0.00120409,0.0008080836],"domain_scores_gemma":[0.9978838,0.0002159257,0.0003002654,0.0006368779,0.0005594732,0.0004036544],"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":[0.00002843521,0.0002072673,0.00008423391,0.00006670295,0.00007567301,0.000008000988,0.04065642,0.00003914566,0.00003080407,0.7843309,0.08645698,0.08801543],"study_design_scores_gemma":[0.00003747707,0.00002855949,0.0005259355,0.0001465525,0.00004295789,1.038047e-7,0.009572288,0.00001160045,0.00003099107,0.6669124,0.3221637,0.0005274665],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05606769,0.002290264,0.002605044,0.4112148,0.06489661,0.001787148,0.000592059,0.003787364,0.456759],"genre_scores_gemma":[0.7100906,0.009209022,0.002299386,0.001281059,0.03751528,0.0001698479,0.0008302928,0.0002596906,0.2383448],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6540229,"threshold_uncertainty_score":0.9999516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3858546014069423,"score_gpt":0.5136275810570362,"score_spread":0.1277729796500939,"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."}}