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The Illusion of Protection: Why Canada’s Growing Push to Ban Social Media for Kids Won’t Work
The momentum behind a social media ban for Canadian minors has been building for months. The federal Liberals voted at their April policy convention to back a minimum age of 16 for social media accounts and AI chatbots, the government’s expert panel on online safety is studying the issue, protesters have now rallied on Parliament Hill calling for it, and on Saturday night, Manitoba Premier Wab Kinew told a Winnipeg fundraiser that his government will be the first in Canada to ban social media and AI chatbots for kids. Kinew did not specify which kids, when it would happen, or how it would be enforced, none of which appeared to matter to the audience. The political appeal of a ban is obvious, since concerns about social media’s effects on young users are widely shared. Yet the policy itself is a terrible idea that will not work. This post examines at least six reasons why an outright age-based ban, particularly one that extends to AI chatbots, is the wrong response to a serious issue.
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.
Lawful Access Heads to Committee: The Opposition Found Its Voice, the Government Never Found Its Defence
After several days of debate in which the opposition to lawful access seemed half-hearted at best, the Conservatives woke up on Monday. MP after MP rose to argue, correctly, that Bill C-22 represents an unprecedented surveillance threat: mandated metadata retention (including location information) for up to a year, security vulnerabilities built into the interception architecture the bill requires, and a weakened legal standard for access to subscriber information. After days of debate with the government visibly struggling to defend its own legislation, this is precisely what the opposition should be targeting (coverage from day one, day two, day three).
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.
Recent Posts
The Illusion of Protection: Why Canada’s Growing Push to Ban Social Media for Kids Won’t Work 
The Law Bytes Podcast, Episode 266: Justin Safayeni on the Ontario Government’s Overnight Evisceration of Access to Information 
AI Without Canada: Why the Heritage Committee’s AI Report Could Lead to Less Canadian Content in the Training Data 
Addressing the AI Policy Challenge: My Appearance before the Standing Senate Committee on Transport and Communications 
Lawful Access Heads to Committee: The Opposition Found Its Voice, the Government Never Found Its Defence
