{"id":"W4404315042","doi":"10.29173/irie536","title":"Conversational Agents and Personal Privacy Harms Case Study","year":2024,"lang":"en","type":"article","venue":"The International Review of Information Ethics","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Internet privacy; Personally identifiable information; Computer science; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009082012,0.0006096311,0.0005160652,0.001475108,0.0138237,0.004795167,0.002219577,0.009369964,0.006838876],"category_scores_gemma":[0.01632447,0.0004668452,0.0009996102,0.001178006,0.01180533,0.00667917,0.008875155,0.006510894,0.0007880496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003602122,"about_ca_system_score_gemma":0.00219057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004158852,"about_ca_topic_score_gemma":0.003527613,"domain_scores_codex":[0.9860131,0.009839637,0.0004393147,0.0007868212,0.001734777,0.001186264],"domain_scores_gemma":[0.9792963,0.01643798,0.00107184,0.001591058,0.0007050881,0.000897799],"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":[0.000251444,0.0005148743,0.006604995,0.0004082742,0.00005048394,0.03152857,0.2705761,0.002298278,0.001584958,0.6419885,0.01494847,0.02924505],"study_design_scores_gemma":[0.0001327731,0.0003494757,0.003150965,0.001054544,0.0001115434,0.05181552,0.2770547,0.01104861,0.008521502,0.1860541,0.4605258,0.0001804603],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5908776,0.003011145,0.1022611,0.05030313,0.0005751486,0.001294028,0.0004794459,0.0003151244,0.2508834],"genre_scores_gemma":[0.9583729,0.000835484,0.02043319,0.002523406,0.0001287076,0.0005746396,0.00008695297,0.00003883277,0.01700593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0138237,"threshold_uncertainty_score":0.04803079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09724793090123471,"score_gpt":0.414695047586919,"score_spread":0.3174471166856843,"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."}}