{"id":"W3153323711","doi":"10.1007/s43154-021-00053-6","title":"Ethics of Corporeal, Co-present Robots as Agents of Influence: a Review","year":2021,"lang":"en","type":"review","venue":"Current Robotics Reports","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University","funders":"","keywords":"Embodied cognition; Robot; Leverage (statistics); Modalities; Human–robot interaction; Set (abstract data type); Human–computer interaction; Artificial intelligence; Computer science; Engineering ethics; Sociology; Engineering; Social science","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.006299806,0.0005268328,0.00370062,0.0001907208,0.0003814582,0.0001045391,0.0007025752,0.001169269,0.0001904081],"category_scores_gemma":[0.01658663,0.0004870373,0.001379323,0.001081402,0.001140568,0.0002192397,0.0003035932,0.002298486,0.00001378045],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002660564,"about_ca_system_score_gemma":0.01089865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001180805,"about_ca_topic_score_gemma":0.0001233338,"domain_scores_codex":[0.9913933,0.001655355,0.002937511,0.000669267,0.002741947,0.0006026165],"domain_scores_gemma":[0.9890311,0.001186334,0.005226944,0.001126739,0.002952886,0.0004760485],"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":[0.000001930197,0.000965444,0.0001977384,0.3091148,0.0007809678,0.0007785205,0.006210212,0.0003873777,2.910527e-7,0.05399898,0.0394102,0.5881535],"study_design_scores_gemma":[0.00003463478,0.00003182203,0.000005177644,0.1571104,0.001135669,0.00003228936,0.00006852151,5.061038e-7,6.931017e-7,0.002752388,0.8384676,0.0003603385],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000002562999,0.9826037,0.00002666625,0.0007834527,0.001926879,0.001499391,0.00004203604,0.00003390682,0.01308139],"genre_scores_gemma":[0.00003576647,0.9985259,0.0001886372,0.0001295024,0.0003160114,0.00003429643,0.00029551,0.00005534728,0.000418993],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7990574,"threshold_uncertainty_score":0.9997581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3049950350388748,"score_gpt":0.5589395080336259,"score_spread":0.2539444729947511,"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."}}