{"id":"W3176616498","doi":"10.29173/irie423","title":"Tangible and Intangible Impact of AI Usage: AI for Information Accessibility","year":2021,"lang":"en","type":"article","venue":"The International Review of Information Ethics","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Intellect; Equity (law); Welfare; Human welfare; Ethical issues; Environmental ethics; Political science; Sociology; Business; Engineering ethics; Economic growth; Public relations; Economics; Engineering; Law; Epistemology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006726145,0.00007826141,0.000199134,0.00007328209,0.0002629205,0.0001882059,0.0003556046,0.0001537675,0.0001607726],"category_scores_gemma":[0.02023879,0.0000566187,0.0001732154,0.0002921752,0.0002759918,0.004157745,0.0000933771,0.0004215475,0.000006127059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001279202,"about_ca_system_score_gemma":0.001739081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009360061,"about_ca_topic_score_gemma":0.0001926618,"domain_scores_codex":[0.9981693,0.0001643614,0.0006856736,0.00005043367,0.0008063227,0.0001239102],"domain_scores_gemma":[0.9931865,0.00104388,0.0005465715,0.000164764,0.005002385,0.00005586986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003417103,0.00003242552,0.0009896749,0.002973157,0.00011458,6.879201e-8,0.02966668,0.00005210325,0.00004042042,0.9357253,0.007569152,0.02280223],"study_design_scores_gemma":[0.001232189,0.0002309718,0.0155688,0.006909118,0.0001700122,0.000007291324,0.01052457,0.001709139,0.002167614,0.4447007,0.5163149,0.0004647259],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.04227581,0.009880559,0.05010874,0.6657226,0.002069503,0.003408155,0.001236015,0.0001094982,0.2251891],"genre_scores_gemma":[0.9373389,0.03597429,0.0009183454,0.02529167,0.000102802,0.00002684757,0.0002210992,0.000004782296,0.0001212178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8950632,"threshold_uncertainty_score":0.9880142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06440760821050519,"score_gpt":0.4804021699332583,"score_spread":0.4159945617227532,"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."}}