{"id":"W4417024830","doi":"10.48550/arxiv.2512.03077","title":"Irresponsible AI: big tech's influence on AI research and associated impacts","year":2025,"lang":"","type":"preprint","venue":"ArXiv.org","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut de Valorisation des Données; Canada First Research Excellence Fund; Canadian Institute for Advanced Research","keywords":"Big data; Software deployment; Odds; TRACE (psycholinguistics); Sustainable development; Key (lock); Social responsibility; Variety (cybernetics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02623703,0.0004332444,0.0004134125,0.004415696,0.006220815,0.01637325,0.0008841699,0.004061671,0.006357802],"category_scores_gemma":[0.04647385,0.0002969328,0.0006187311,0.004173055,0.02669922,0.01059348,0.008501897,0.0061078,0.0007308818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007296714,"about_ca_system_score_gemma":0.006806246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003140414,"about_ca_topic_score_gemma":0.004342236,"domain_scores_codex":[0.9743526,0.01519315,0.0006321832,0.001413315,0.006751408,0.00165728],"domain_scores_gemma":[0.8608543,0.1042441,0.01132107,0.006056843,0.01040297,0.00712062],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007587185,0.00006512653,0.02124151,0.000476772,0.00009744825,0.0005908301,0.01214199,0.0008287336,0.0007353995,0.8724275,0.03010266,0.06121613],"study_design_scores_gemma":[0.00002099835,0.00008207883,0.01903231,0.001253792,0.00007109695,0.0003967221,0.01449798,0.001171111,0.001400484,0.6496106,0.3123704,0.00009238895],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1237348,0.02939348,0.01594531,0.4628049,0.002895071,0.00006504324,0.0002471952,0.000218385,0.3646959],"genre_scores_gemma":[0.9380213,0.01425562,0.002498959,0.03523258,0.00271424,0.00006021786,0.00008294294,0.0001669227,0.006967262],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.973763,"threshold_uncertainty_score":0.1387563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2081706080393426,"score_gpt":0.4794667799630349,"score_spread":0.2712961719236923,"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."}}