LEAF and The Citizen Lab Joint Submission on Toronto Police Use of AI Policy

In December 2021, LEAF and The Citizen Lab have made a joint submission to the Toronto Police Services Board on its draft policy concerning police use of artificial intelligence (AI) technologies.

The submission, written by Suzie Dunn, Kristen Thomasen, and Kate Robertson, urges the Board to centre precaution, substantive equality, human rights, privacy protections, transparency, and accountability in its policy. In the submission, LEAF and The Citizen Lab implore the Board to continue to seek out the guidance and expertise of:

• AI and technology scholars and advocates;
• equality and human rights experts;
• affected communities and their members, including historically marginalized communities; and
• other relevant stakeholders when developing and implementing policies related to the adoption and use of AI by the TPS today, and into the future.

Both organizations also recommend that the Board place an immediate moratorium on law enforcement use of algorithmic policing technologies that do not meet minimum prerequisite conditions of reliability, necessity, and proportionality.

This joint submission was written and reviewed by a group of experts in the legal regulation of AI, technology-facilitated violence, equality, and the use of AI systems by law enforcement in Canada.

The recommendations and comments in the submission focus on the following key observations:

1. Police use of AI technologies must not be seen as inevitable
2. A commitment to protecting equality and human rights must be integrated more thoroughly throughout the Board policy and its AI analysis procedures
3. Inequality is embedded in AI as a system in ways that cannot be mitigated through a policy only dealing with use
4. Having more accurate AI systems does not mitigate inequality
5. The Board must not engage in unnecessary or disproportionate mass collection and analysis of data
6. The Board’s AI policy should provide concrete guidance on the proactive identification and classification of risk
7. The Board’s AI policy must ensure expertise in independent vetting, risk analysis, and human rights impact analysis
8. The Board should be aware of assessment challenges that can arise when an AI system is developed by a private enterprise
9. The Board must apply the draft policy to all existing AI technologies that are used by, or presently accessible to, the Toronto Police Service

LEAF’s work on this submission is part of its Technology-Facilitated Violence Project, bringing together feminist lawyers and scholars to advance equality-enhancing responses to technology-facilitated violence against women and gender-diverse people.

LEAF would like to thank Kristen Thomasen, Suzie Dunn, Kate Robertson, Cynthia Khoo, Ngozi Okidegbe, and Christopher Parsons for their collaboration on this submission. Read the full submission here.