{"id":"W4394875689","doi":"10.1016/j.bushor.2024.04.012","title":"From HAL to GenAI: Optimizing chatbot impacts with CARE","year":2024,"lang":"en","type":"article","venue":"Business Horizons","topic":"AI in Service Interactions","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Chatbot; Accountability; Productivity; Empowerment; Knowledge management; Adaptability; Macro; Creativity; Perspective (graphical); Computer science; Business; Engineering ethics; Engineering; Psychology; Political science; Management; Artificial intelligence; Economics","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":[0.00004830235,0.0002111669,0.000168506,0.0002215641,0.0001545504,0.0007866484,0.0007717581,0.00006336333,0.00005817449],"category_scores_gemma":[0.00002766185,0.0001741016,0.00004789387,0.00154524,0.00002202327,0.001236642,0.0003309263,0.0001831563,0.0005765226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001520737,"about_ca_system_score_gemma":0.0002606756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001625991,"about_ca_topic_score_gemma":0.0005340485,"domain_scores_codex":[0.9985765,0.00002329363,0.0001688714,0.0005755349,0.0002957799,0.0003599729],"domain_scores_gemma":[0.9986217,0.0001153173,0.00003280482,0.0007174336,0.0003263141,0.0001864535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003049216,0.0007759212,0.00289521,0.002008995,0.001593317,0.007102292,0.2209514,0.0562457,0.07577081,0.1056043,0.08094727,0.4457999],"study_design_scores_gemma":[0.002710272,0.00179818,0.1073073,0.01163438,0.0006580141,0.001556354,0.01939733,0.1754681,0.04123148,0.004850952,0.6257184,0.007669236],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1026706,0.0008665665,0.8758543,0.01267987,0.002954412,0.0002647047,0.00005174765,0.0009667185,0.003691083],"genre_scores_gemma":[0.8605599,0.00001888099,0.1379251,0.000469804,0.0007509856,0.00005853119,0.00002250246,0.00004299902,0.0001513007],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7578893,"threshold_uncertainty_score":0.7585668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01122560232296882,"score_gpt":0.2559116069016404,"score_spread":0.2446860045786716,"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."}}