Canada Protocol: an ethical checklist for the use of Artificial Intelligence in Suicide Prevention and Mental Health

TL;DR

The Canada Protocol MHSP provides an ethical checklist to guide AI use in mental health and suicide prevention, addressing key ethical risks through expert-validated recommendations.

Contribution

It introduces a validated ethical checklist specifically designed for AI applications in mental health and suicide prevention, filling a gap in current guidelines.

Findings

38 out of 43 recommendations retained after Delphi validation

Checklist covers privacy, security, risks, biases, and system description

Most users found the checklist relevant and adaptable

Abstract

Introduction: To improve current public health strategies in suicide prevention and mental health, governments, researchers and private companies increasingly use information and communication technologies, and more specifically Artificial Intelligence and Big Data. These technologies are promising but raise ethical challenges rarely covered by current legal systems. It is essential to better identify, and prevent potential ethical risks. Objectives: The Canada Protocol - MHSP is a tool to guide and support professionals, users, and researchers using AI in mental health and suicide prevention. Methods: A checklist was constructed based upon ten international reports on AI and ethics and two guides on mental health and new technologies. 329 recommendations were identified, of which 43 were considered as applicable to Mental Health and AI. The checklist was validated, using a two round Delphi Consultation. Results: 16 experts participated in the first round of the Delphi Consultation and 8 participated in the second round. Of the original 43 items, 38 were retained. They concern five categories: "Description of the Autonomous Intelligent System" (n=8), "Privacy and Transparency" (n=8), "Security" (n=6), "Health-Related Risks" (n=8), "Biases" (n=8). The checklist was considered relevant by most users, and could need versions tailored to each category of target users.