{"id":"W4380875660","doi":"10.1145/3563359.3597383","title":"Ethical issues in explanations of personalized recommender systems","year":2023,"lang":"en","type":"article","venue":"","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Recommender system; Transparency (behavior); Computer science; Ethical issues; Personalization; Data science; Engineering ethics; World Wide Web; Computer security; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.1188408,0.0007850698,0.0007905972,0.001786617,0.005474423,0.009789786,0.002379855,0.01408444,0.005147717],"category_scores_gemma":[0.3580188,0.0008590794,0.0009320661,0.001280169,0.02101906,0.01410868,0.006341466,0.008673616,0.0007321411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005988704,"about_ca_system_score_gemma":0.007967887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003504936,"about_ca_topic_score_gemma":0.003164349,"domain_scores_codex":[0.7532884,0.2171879,0.006577786,0.003516109,0.01703221,0.002397723],"domain_scores_gemma":[0.4303425,0.5031211,0.0196937,0.02362539,0.02063001,0.002587311],"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":[0.0001871148,0.00009223328,0.003095985,0.0005291174,0.00006737881,0.0005653974,0.02139965,0.003771453,0.0003829869,0.9056882,0.01044958,0.05377093],"study_design_scores_gemma":[0.000162083,0.0001216291,0.001152544,0.001129489,0.0000756869,0.0005867547,0.004696554,0.009446303,0.00148303,0.8730174,0.1079979,0.0001306871],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0716868,0.01330723,0.4963074,0.3276605,0.002467353,0.0009661979,0.0003398305,0.0005758344,0.08668888],"genre_scores_gemma":[0.8359783,0.00309005,0.1337895,0.0180203,0.0009917659,0.0008081109,0.0001620646,0.0001552709,0.007004605],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1188408,"threshold_uncertainty_score":0.6284979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08764068147313261,"score_gpt":0.3639379450393281,"score_spread":0.2762972635661954,"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."}}