{"id":"W4416083181","doi":"10.1016/j.tics.2025.10.011","title":"Identifying indicators of consciousness in AI systems","year":2025,"lang":"en","type":"review","venue":"Trends in Cognitive Sciences","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute; Canadian Institute for Advanced Research","funders":"H2020 European Research Council; Australian Research Council; European Research Council; Fonds de recherche du Québec; HORIZON EUROPE Framework Programme; Agence Nationale de la Recherche; Templeton World Charity Foundation; Open Philanthropy Project; Social Sciences and Humanities Research Council of Canada; UK Research and Innovation; Government of the United Kingdom; Canadian Institute for Advanced Research","keywords":"Consciousness; Artificial consciousness; Cognition; Neural system; Qualia","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001627927,0.001308957,0.001526428,0.002842806,0.0003076507,0.001964689,0.001309482,0.001876427,0.00271704],"category_scores_gemma":[0.003581762,0.000385093,0.00048222,0.002777519,0.00176431,0.003736693,0.001234457,0.0024423,0.001474119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493422,"about_ca_system_score_gemma":0.002042387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002163887,"about_ca_topic_score_gemma":0.002502164,"domain_scores_codex":[0.9996568,0.00008330463,0.00004685283,0.00008087518,0.0001062514,0.00002593732],"domain_scores_gemma":[0.9983872,0.001125041,0.0001213671,0.00005307898,0.0002634283,0.00004992666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005411826,0.00003028357,0.000217772,0.01324541,0.00007191164,0.00006793987,0.00006529627,0.0003989991,0.0007447531,0.01484226,0.01142041,0.9588408],"study_design_scores_gemma":[0.00003479145,0.0001297499,0.002827834,0.01760305,0.0003447074,0.001133122,0.0001883921,0.0008784089,0.001978905,0.06877936,0.9060124,0.00008940659],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00007834213,0.9978516,0.0007020969,0.0003463308,0.0001544879,0.000003975988,0.00001115023,0.000008466567,0.0008435257],"genre_scores_gemma":[0.001440051,0.9965076,0.0008971454,0.0003187267,0.0004121726,0.000009858735,0.00002990466,0.000003387257,0.0003810828],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002842806,"threshold_uncertainty_score":0.01083559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3183444491442382,"score_gpt":0.4995573497372415,"score_spread":0.1812129005930033,"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."}}