# Are Treatment Services Ready for the Use of Big Data Analytics and AI in Managing Opioid Use Disorder?

## TL;DR

This paper discusses the challenges of using big data and AI in treating opioid use disorder, focusing on ethical and practical issues.

## Contribution

The paper outlines 8 key challenges for implementing big data and AI in opioid use disorder treatment services.

## Key findings

- Big data and AI face ethical and practical challenges in opioid use disorder treatment.
- Eight key challenges include data transparency, clinical validation, and addressing digital exclusion and bias.
- Implementation requires careful consideration of ethical and clinical implications.

## Abstract

In this viewpoint, we explore the use of big data analytics and artificial intelligence (AI) and discuss important challenges to their ethical, effective, and equitable use within opioid use disorder (OUD) treatment settings. Applying our collective experiences as OUD policy and treatment experts, we discuss 8 key challenges that OUD treatment services must contend with to make the most of these rapidly evolving technologies: data and algorithmic transparency, clinical validation, new practitioner-technology interfaces, capturing data relevant to improving patient care, understanding and responding to algorithmic outputs, obtaining informed patient consent, navigating mistrust, and addressing digital exclusion and bias. Through this paper, we hope to critically engage clinicians and policy makers on important ethical considerations, clinical implications, and implementation challenges involved in big data analytics and AI deployment in OUD treatment settings.