{"id":"W4414662698","doi":"10.2139/ssrn.5468868","title":"Communicating Uncertainty Can Increase AI Adoption","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Set (abstract data type); Range (aeronautics); Outcome (game theory); Recommender system; Uncertainty reduction theory; Cheap talk","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":[0.005987957,0.0004254591,0.0003337825,0.001029513,0.001311751,0.003669302,0.0006353644,0.003270115,0.01709087],"category_scores_gemma":[0.06789873,0.0003623314,0.0004924632,0.001195226,0.001670773,0.004708868,0.002794144,0.003051876,0.001144832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118545,"about_ca_system_score_gemma":0.001066814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001072445,"about_ca_topic_score_gemma":0.001375181,"domain_scores_codex":[0.9958897,0.002078437,0.000165546,0.000431654,0.0009752457,0.0004593987],"domain_scores_gemma":[0.8904073,0.09002464,0.008852643,0.005647172,0.003020698,0.002047519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001600716,0.002122721,0.1662863,0.0009146551,0.0005298082,0.002242339,0.02007692,0.02189861,0.01047717,0.5071868,0.0169297,0.2497341],"study_design_scores_gemma":[0.0002064623,0.0005634077,0.08333595,0.0001901911,0.0003108323,0.0005572786,0.007757824,0.03616264,0.004462838,0.8252316,0.04111565,0.0001053492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7634554,0.001962268,0.03486146,0.01897497,0.0003061228,0.0001327278,0.0002510144,0.0003831143,0.1796729],"genre_scores_gemma":[0.996003,0.0002124678,0.00158032,0.0004194024,0.00009221461,0.00002669065,0.0000302707,0.0000229212,0.001612649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01709087,"threshold_uncertainty_score":0.05717462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193665300640281,"score_gpt":0.2935442126060599,"score_spread":0.2741776825420318,"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."}}