{"id":"W7118197459","doi":"10.1109/aiccsa66935.2025.11315298","title":"Privacy in Generative AI: Understanding User Concerns, Trust, and Awareness","year":2025,"lang":"","type":"article","venue":"","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Trustworthiness; Information privacy; Generative grammar; Privacy software; Perception; Privacy by Design; Generative model","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":[0.01902272,0.0002732291,0.0002545391,0.001657562,0.002831564,0.006861542,0.000580069,0.001439797,0.0009684594],"category_scores_gemma":[0.04776059,0.0003680724,0.0003887163,0.0009188246,0.008987047,0.008106369,0.004230252,0.002019985,0.0001593708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002566289,"about_ca_system_score_gemma":0.001664824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003570559,"about_ca_topic_score_gemma":0.002152669,"domain_scores_codex":[0.9770367,0.01912746,0.00056545,0.0005276895,0.002011355,0.0007314013],"domain_scores_gemma":[0.933341,0.05164087,0.006586794,0.003247848,0.003448882,0.001734594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001625015,0.0001852272,0.1608746,0.0001679287,0.00006346499,0.0004793802,0.731423,0.0008295611,0.001608447,0.05288241,0.0007859765,0.05053753],"study_design_scores_gemma":[0.0000453741,0.0004427408,0.1027138,0.0007075972,0.000147775,0.002013474,0.6529288,0.01611796,0.003096016,0.174769,0.04682898,0.0001885744],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9583021,0.000752083,0.01905105,0.004921737,0.00001740489,0.00003805106,0.00001731094,0.00004411412,0.01685617],"genre_scores_gemma":[0.998928,0.00009949631,0.0006610785,0.0001627021,0.000003409268,0.000006374377,0.000004351054,0.000003789975,0.0001307979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01902272,"threshold_uncertainty_score":0.1006029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1530219537655449,"score_gpt":0.4384995282699112,"score_spread":0.2854775745043663,"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."}}