ALGORITHMIC BIAS IN AI-ASSISTED PSYCHIATRIC DIAGNOSIS: A STRUCTURED REVIEW OF DEMOGRAPHIC DISPARITIES AND GOVERNANCE FAILURES
DOI:
https://doi.org/10.31435/ijitss.4(52).2026.6583Keywords:
Algorithmic Bias , Artificial Intelligence , Psychiatric Diagnosis , Health Equity , Demographic Disparities , Clinical GovernanceAbstract
Background: The use of artificial intelligence (AI) and machine learning (ML) for psychiatric diagnostic aid during clinical triage and mental health assessment has a potential value that is hard to underestimate. The use of these tools will raise many socio-technical issues concerning the biases of the algorithms. Such biases may be especially harmful for those patient populations that are already most vulnerable.
Objective: The purpose of this study is to identify the degree of biases of algorithms for AI in mental health tools, understand how the existing demographic imbalances impact the diagnostic gap and identify the existing regulatory crisis that allows these systemic clinical hazards.
Method: A structured review of the literature was performed and research on the study was limited to articles published between the years 2018 and 2026 on the databases of PubMed/MEDLINE and Google Scholar. A thematic synthesis framework was used to study evidence through three domains: diagnostic disparities, demographic imbalances, and regulatory inadequacy.
Results: Observed literature indicates that AI tools for diagnosis have great variability and a lack of significant accuracy toward different racial, gender, and socioeconomic groups. The review found that the lack of existing governance frameworks allows systemic clinical inequities to persist.
Conclusions: Uncontrolled algorithmic bias toward psychiatric AI tools will create direct and significant clinical harm. These will lead to exacerbated health inequities and will require severe policy shifts. Standardized algorithm auditing and human-in-the-loop clinical pathways will also be needed.
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Copyright (c) 2026 Mateusz Lis, Maryan Liasota , Eliza Zofia Kabat , Michalina Justyna Kozłowska, Krzysztof Konopka, Maciej Kamil Majchrzak, Faustyna Magdalena Kołodziej, Alicja Kwiatkowska, Jakub Juskowiak, Zuzanna Julia Komin
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