Just over a month ago, the Ford government tabled Bill 97, an omnibus bill with provisions fundamentally restructuring Ontario’s access to information system. Information and Privacy Commissioner Patricia Kosseim responded with alarm, but the government rushed ahead with no hearings or public debate. The most significant rewrite of Ontario’s access to information regime in nearly forty years became law within weeks. Justin Safayeni, a partner at Stockwoods LLP in Toronto, is one of Canada’s leading practitioners in access to information and media law. He joins me on the Law Bytes podcast to make sense of what just happened and what comes next.
Latest Posts
AI Without Canada: Why the Heritage Committee’s AI Report Could Lead to Less Canadian Content in the Training Data
When I appeared before the Standing Committee on Canadian Heritage last fall for its study on AI and the creative industries, I emphasized that the large language models and generative AI systems that are reshaping how people access information, culture, and entertainment are only as representative as the data on which they are trained. If Canadian works, perspectives, and cultural content are absent from those models, Canada risks disappearing in the AI-mediated world. The committee’s report, released this month, acknowledges this concern, but its lead recommendation risks making the situation worse.
Addressing the AI Policy Challenge: My Appearance before the Standing Senate Committee on Transport and Communications
Earlier this week, I appeared before the Standing Senate Committee on Transport and Communications as part of its study on AI regulation. This follows earlier appearances before the House of Commons Heritage and Industry committees on the same issue. The hearing led to robust exchanges with multiple Senators on the intersection of AI policy with issues such as privacy, copyright, online harms, and sovereignty. I plan to post clips from the hearing in a future Law Bytes podcast, but in the meantime, my opening statement provides a good sense of my views on AI regulation with respect to privacy, copyright, and the need for an AI Transparency Act. A video of the opening statement is embedded below, followed by the text.
Is Data De-Identification Dead?: Why the AI Privacy Risk Isn’t What It Learns, But What It Figures Out
In 1997, an MIT graduate student named Latanya Sweeney stunned the privacy world by matching publicly available voter rolls with hospital records stripped of names and addresses to identify the supposedly anonymous medical history of the then-governor of Massachusetts. Three years later, she expanded on that finding by demonstrating that 87 per cent of the U.S. population could be uniquely identified using just three data points: ZIP code, date of birth and gender.
My Globe and Mail op-ed notes that Ms. Sweeney’s work shaped privacy frameworks worldwide, which responded with de-identification standards designed to manage the risk by removing obvious identifiers, applying statistical tests and treating the resulting data as safe to use. Indeed, a core tenet of modern privacy regulation rests on the premise that de-identified data can be used, disclosed and commercialized without compromising individual privacy.


















