{"id":"W4396218845","doi":"10.1145/3637396","title":"Seamful XAI: Operationalizing Seamful Design in Explainable AI","year":2024,"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":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsoft (Canada)","funders":"Universitas Brawijaya","keywords":"Sociotechnical system; Computer science; Operationalization; Leverage (statistics); Process (computing); Context (archaeology); Knowledge management; 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":[0.02543704,0.001168572,0.0003933327,0.002102118,0.002869085,0.007663709,0.002583846,0.003281421,0.004913976],"category_scores_gemma":[0.05853297,0.001167608,0.001286707,0.000865993,0.01423808,0.01058498,0.01106167,0.003577221,0.0007418529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00298171,"about_ca_system_score_gemma":0.004393512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001950695,"about_ca_topic_score_gemma":0.00225156,"domain_scores_codex":[0.9766744,0.01768646,0.001098305,0.00170477,0.002068242,0.0007677919],"domain_scores_gemma":[0.9498491,0.03108216,0.003415286,0.01196035,0.002532909,0.001160214],"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":[0.0002959888,0.0005924863,0.0157441,0.001578168,0.0001359257,0.0008837959,0.1566615,0.02613865,0.01775301,0.6267182,0.003082384,0.1504159],"study_design_scores_gemma":[0.0001908697,0.0008461393,0.005082277,0.001380423,0.0002413119,0.001255428,0.03035799,0.130958,0.02352528,0.67437,0.1315282,0.0002641093],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06748876,0.0002806609,0.9063661,0.0030136,0.00007600465,0.0008129158,0.00009979386,0.002078896,0.01978326],"genre_scores_gemma":[0.5031955,0.0001698468,0.4921502,0.0005058029,0.00002059336,0.0008289477,0.0001428857,0.0003337693,0.002652472],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02543704,"threshold_uncertainty_score":0.1345255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1375082652121015,"score_gpt":0.432029780617969,"score_spread":0.2945215154058675,"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."}}