{"id":"W3006911910","doi":"10.1108/intr-12-2019-0503","title":"Collaborating with technology-based autonomous agents","year":2020,"lang":"en","type":"article","venue":"Internet Research","topic":"AI in Service Interactions","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Originality; Autonomous agent; Leverage (statistics); Unintended consequences; Transparency (behavior); Knowledge management; Computer science; Set (abstract data type); Sociology; Position paper; Design science research; Key (lock); Psychology; Artificial intelligence; Social psychology; Epistemology; Information system; Engineering; World Wide Web","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":[0.01801638,0.0004397576,0.0003816861,0.001129311,0.006300676,0.008820142,0.001821792,0.001979711,0.009479089],"category_scores_gemma":[0.03727074,0.0002661747,0.0006045048,0.0009896641,0.005429883,0.008273554,0.009331994,0.002258388,0.001745891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001877223,"about_ca_system_score_gemma":0.003221968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001279328,"about_ca_topic_score_gemma":0.001257839,"domain_scores_codex":[0.9672879,0.02588158,0.0005402888,0.001976315,0.003119559,0.001194246],"domain_scores_gemma":[0.9234205,0.05671884,0.004966807,0.006369836,0.004120983,0.004402986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0004990894,0.0008946978,0.04686935,0.00179368,0.0002684127,0.001656714,0.4141304,0.004222048,0.009534319,0.2344873,0.02653573,0.2591083],"study_design_scores_gemma":[0.0001644128,0.0006492342,0.01319272,0.0009865991,0.0001727393,0.0009698206,0.2007828,0.00840262,0.005274897,0.1228321,0.6464069,0.0001651335],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5707765,0.002970262,0.1332507,0.03776157,0.001019965,0.0009243955,0.0001487359,0.0004696812,0.2526782],"genre_scores_gemma":[0.9649208,0.0007778747,0.01939986,0.002311144,0.0001658536,0.0003074781,0.00008654641,0.00008038873,0.01195013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01801638,"threshold_uncertainty_score":0.09528089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1027348476715138,"score_gpt":0.3873943974324964,"score_spread":0.2846595497609825,"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."}}