Préjudices algorithmiques envers les peuples autochtones au Canada : disparités documentées dans la justice, la protection de l'enfance et le maintien de l'ordre

AI systems are being applied to Indigenous peoples in Canada in policing, data collection, and service delivery, often without cross-cultural validation, community governance, or recognition of First Nations data sovereignty.

Legal and institutional context

Algorithmic and actuarial tools have a documented history of producing discriminatory outcomes for Indigenous peoples in Canada. In Ewert v. Canada (2018 SCC 30), the Supreme Court of Canada ruled 7-2 on the statutory claim that the Correctional Service of Canada breached its obligation under s. 24(1) of the Corrections and Conditional Release Act to take all reasonable steps to ensure that any information about an offender that it uses is as accurate, up to date and complete as possible. The tools at issue — the PCL-R, VRAG, SORAG, Static-99, and VRS-SO — were actuarial and psychological scoring instruments developed and validated on predominantly non-Indigenous populations. While these specific instruments are rule-based tools outside CAIM's AI system scope, the ruling establishes a legal precedent directly relevant to AI-based risk assessment: systems trained or validated without adequate representation of Indigenous populations may breach statutory obligations when applied to Indigenous peoples.

The Ontario Human Rights Commission's 2018 report "Interrupted Childhoods" found Indigenous children overrepresented in admissions into care at 93% of agencies surveyed, with proportions 2.6 times higher than their share of the child population. The report identified risk assessment tools reflecting "White, Western, Christian notions of acceptable child rearing" as a contributing factor. A separate analysis (Fallon et al., 2016, CWRP Information Sheet #176E) found that Aboriginal children were more than 130% more likely to be investigated than White children and 168% more likely to be placed in out-of-home care. The specific tools involved are structured decision-making instruments rather than AI systems, but the documented pattern of cross-cultural bias in risk scoring has direct implications for AI-based tools now entering these domains.

AI-specific harms

The Citizen Lab at the University of Toronto and the International Human Rights Program published "To Surveil and Predict" (2020), a human rights analysis of algorithmic policing in Canada. The report documented AI-driven predictive policing tools and bail risk algorithms being used in ways that affect Indigenous peoples, including monitoring of Indigenous rights protesters. The report stated that historical policing data reflects patterns of systemic discrimination, and identified negative feedback loops: communities with higher rates of police contact generate more data, which machine learning models interpret as indicating higher risk — a dynamic the report characterized as reinforcing discriminatory patterns.

The International Association of Privacy Professionals has reported that information from individuals using AI-driven services in remote Indigenous communities is "routinely absorbed to train and refine AI systems" without community governance. The First Nations Information Governance Centre's Data Sovereignty Research Collaborative addresses AI and big data within the context of OCAP principles (Ownership, Control, Access, Possession) — a First Nations data governance framework.

First Nations governance responses

The Assembly of First Nations submitted a formal brief to the House of Commons Standing Committee on Industry and Technology (INDU) regarding Bill C-27 (AIDA), stating that "AI has the potential to destroy First Nations' cultures, threaten First Nations' security, and increase demand for our resources." The AFN stated that there had been no Nation-to-Nation consultation between Canada and First Nations on the legislation. Bill C-27 subsequently died on the Order Paper when Parliament was prorogued on January 6, 2025; the AFN's position on Nation-to-Nation consultation applies to any successor AI legislation.

The Chiefs of Ontario Research and Data Management Sector published a research paper in 2024 analyzing the effects of AI on First Nations in Ontario, describing AI as "a powerful and disruptive technology" that comes "paired with serious risks for First Nations."

The First Nations of Quebec and Labrador Health and Social Services Commission (CSSSPNQL) published a position paper on digital and AI ethics, establishing guidelines to "guide digital development in harmony with the values of First Nations."