“E3 of AI”: Equity, Errors, and Ethics of Artificial Intelligence in Vulnerable Populations with Substance Use Disorder-View Presentation

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The session, hosted on a Saturday morning, tackled the topics of equity, errors, and ethics of artificial intelligence (AI) in vulnerable populations with substance use disorders (SUD). Chaired by Jacques Ambrose, the session featured esteemed professionals, including Dr. Colin Burke, Dr. Silvia Franco Corso, and Dr. Jehede, who examined AI's role in clinical practice, psychiatry, and specific marginalized communities.<br /><br />Dr. Colin Burke presented cases involving youth experiencing homelessness. He emphasized the complexities of accurately diagnosing psychiatric conditions in such populations, given the high prevalence of trauma and substance use. He discussed AI's potential to improve access to subspecialty SUD care, enhance psychiatric diagnosis accuracy, and provide between-session support for individuals. However, he stressed concerns about the quality of AI-based tools, potential development of a two-tiered care system, and maintaining safety and effective therapeutic relationships.<br /><br />Dr. Jehede discussed health inequities and AI's potential to perpetuate racial disparities within a pre-existing, structurally biased healthcare system. He highlighted examples, such as stigmatizing language in electronic health records affecting AI outcomes and called for community collaboration and equity-focused AI algorithms.<br /><br />Lastly, Dr. Franco Corso talked about AI applications in assisting individuals with disabilities who also have SUD. She provided examples of AI technologies that facilitate daily activities and therapeutic interventions for disabled individuals, while cautioning against challenges like under-representation in training data and the risk of exacerbating inequities.<br /><br />Overall, the session underscored the importance of integrating AI with an equity-focused approach, ensuring ethical and culturally sensitive implementations, and addressing the socio-economic barriers present in the healthcare system.

Keywords

artificial intelligence

equity

ethics

substance use disorders

vulnerable populations

psychiatric diagnosis

health inequities

racial disparities

community collaboration

AI applications

disabled individuals

socio-economic barriers