Artificial Intelligence and Stigma in Addiction Research: Insights From the HEALing Communities Study Coalition MeetingsArtificial Intelligence and Stigma in Addiction Research: Insights From the HEALing Communities Study Coalition Meetings
Addiction Medicine: Beyond the Abstract
Shawn McNeil, MD talks with Dr Nabila El-Bassel about stigma surrounding medication for opioid use disorder and the use of AI in addiction research. Their discussion focuses on structural inequities, community-engaged science, and practical advice for using AI while keeping human judgement central.
21:47•10 Apr 2026
AI, Stigma and MOUD: Dr Nabila El-Bassel on Rethinking Addiction Research
Episode Overview
- Stigma around MOUD is widespread and often rooted in the belief that it is simply replacing one drug with another, rather than recognising it as life-sustaining treatment.
- Stigma and inequity frequently overlap, especially for Black, Hispanic and other marginalised communities facing racism, poverty and criminal legal involvement.
- Efforts to reduce stigma should focus on specific settings such as drug treatment programmes, healthcare systems, pharmacies and policy environments.
- AI can speed up analysis of large, qualitative datasets and support real-time learning during community-engaged addiction research.
- A human-centred approach is crucial: AI should assist, while researchers, clinicians and community partners stay actively involved to question outputs and protect context, privacy and consent.
“"Ai should support the research, not replace the human judgment."”
How do people find strength in their journey to sobriety? This conversation looks at that question from a research angle, asking how stigma and technology shape addiction care. Host Shawn McNeil, MD, chats with Dr Nabila El-Bassel, a leading social and behavioural addiction researcher from Columbia University, about her article on artificial intelligence and stigma in the HEALing Communities Study.
The episode is aimed at clinicians, researchers, and anyone curious about how evidence and community experience come together in addiction medicine. Dr El-Bassel explains why she was drawn to addiction research: to understand how "structural drivers such as stigma, poverty, homelessness, incarceration" block access to treatment, and to work closely with communities and people with lived experience. The heart of the discussion is stigma around medication for opioid use disorder (MOUD).
She notes that many still see MOUD as "replacing one drug with another" instead of recognising that medications like methadone or buprenorphine "help them to survive" and live their lives. The talk digs into why stigma shows up so strongly around MOUD, especially for people of colour, where it overlaps with racism, poverty, and criminal legal involvement.
Dr El-Bassel argues that reducing stigma has to focus on the systems people actually face: "drug treatment programs, healthcare system, pharmacies" and policies that label and exclude. You’ll also hear a clear, no-nonsense take on AI in addiction research.
She highlights how AI can speed up analysis of interviews, focus groups and community data, and even feed results back in real time, but stresses that "ai should support the research, not replace the human judgment." Keeping "humans in the loop" is central to avoiding bias, loss of context, and privacy problems. The episode closes with practical advice for emerging clinicians and researchers: take stigma seriously, centre equity, and use AI tools wisely.
If you care about making addiction treatment fairer and more effective, what changes could you bring into your own work after hearing this?
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