{"id":"W4382136296","doi":"10.1108/dts-03-2023-0018","title":"Artificial intelligence, task complexity and uncertainty: analyzing the advantages and disadvantages of using algorithms in public service delivery under public administration theories","year":2023,"lang":"en","type":"article","venue":"Digital Transformation and Society","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"École Nationale d'Administration Publique","funders":"","keywords":"Transaction cost; Public service; Public sector; Equity (law); New public management; Service (business); Database transaction; Economics; Computer science; Management science; Sociology; Public relations; Business; Marketing; Political science; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.001047543,0.00009500355,0.0001427227,0.00005553582,0.0007583261,0.0008075544,0.00008087201,0.000104412,0.000003605283],"category_scores_gemma":[0.0001068161,0.00007710038,0.00004726715,0.0005847864,0.0008888455,0.002303632,0.00002871542,0.0001506876,3.734445e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003242403,"about_ca_system_score_gemma":0.000134312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003251513,"about_ca_topic_score_gemma":0.00255209,"domain_scores_codex":[0.9990575,0.00008979273,0.000273968,0.0001250849,0.0002340238,0.0002196437],"domain_scores_gemma":[0.9992825,0.0003393267,0.00007760574,0.00005122468,0.0001634529,0.00008588765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001067847,0.0000374253,0.003838805,0.00008093935,0.00003489891,3.408644e-7,0.1326809,0.00003551861,0.00005572628,0.8156739,0.00000376496,0.04754706],"study_design_scores_gemma":[0.0001523733,0.00004835024,0.0122858,0.00004706077,0.00002053215,0.000001649187,0.5609569,0.02254827,0.00005161816,0.4029724,0.0006770552,0.000237976],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738278,0.0000993864,0.003507102,0.02106358,0.00004694717,0.0002028613,0.0000871857,0.00003984867,0.001125336],"genre_scores_gemma":[0.9975539,0.002078189,0.00006730016,0.0002053818,0.00003031705,0.00000285166,0.00005123896,0.000004907681,0.000005925032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.428276,"threshold_uncertainty_score":0.7787266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1288499425704819,"score_gpt":0.3781023931886917,"score_spread":0.2492524506182097,"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."}}