{"id":"W3176040021","doi":"10.1007/s10676-021-09599-7","title":"From human resources to human rights: Impact assessments for hiring algorithms","year":2021,"lang":"en","type":"article","venue":"Ethics and Information Technology","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":122,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Accountability; Human rights; Audit; Algorithm; Law and economics; Public relations; Political science; Economics; Computer science; Law; Accounting","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001492102,0.00009850684,0.0001709785,0.0002050774,0.002923563,0.0004368782,0.0002145606,0.0007229603,0.00006640804],"category_scores_gemma":[0.001212647,0.00009520343,0.00005260781,0.0003277003,0.0002729547,0.001167928,0.0001138719,0.0007689511,0.00000990616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001009481,"about_ca_system_score_gemma":0.0001693055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005435912,"about_ca_topic_score_gemma":0.003076974,"domain_scores_codex":[0.9988996,0.00008749145,0.000296361,0.0001334299,0.0003000477,0.0002830175],"domain_scores_gemma":[0.9986176,0.000289532,0.0001378472,0.0001613012,0.000672162,0.0001214979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000425802,0.00002373088,0.0003463183,0.00001731602,0.00005123236,0.000001145514,0.06411126,0.00000404561,0.000608876,0.9229448,0.001885902,0.01000114],"study_design_scores_gemma":[0.000334172,0.0001644739,0.001158782,0.0000461285,0.00001254405,4.499012e-7,0.01735472,0.00003464761,0.001017442,0.501738,0.4779561,0.000182521],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8793523,0.00008504139,0.005104286,0.07984909,0.000349795,0.0004682802,0.0001241882,0.000309292,0.03435777],"genre_scores_gemma":[0.9926799,0.00006058468,0.004806403,0.001805771,0.0002147081,0.00002683101,0.00007877428,0.000006859066,0.0003201648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4760702,"threshold_uncertainty_score":0.9983745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0621558161986932,"score_gpt":0.4625187048818698,"score_spread":0.4003628886831766,"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."}}