This story contains details about domestic violence that some readers may find disturbing.

For years, there was a box on a back shelf of P’s house in Edmonton labelled “insurance.” (For reasons of privacy, we are using this initial only.) Her husband at the time thought it contained paperwork, but P had filled it with a different kind of insurance: a physical record of smashed phones, broken eyeglasses, and photographs of the bruises his violent episodes had left on her body. “I had a circle of blue bruises around my mouth because he would cover my mouth and smother me,” she told me.

Photographs, videos, and audio recordings are highly persuasive to judges and juries. When a crime occurs in private, with no witnesses, a court contest is a tussle in which two stories compete to offer the most plausible explanation of the same facts. Photographs and audio recordings join seemingly unimpeachable objectivity with emotional impact: one study says combining visual and oral testimony can increase information retention among jurors by 650 percent.

Criminal defence lawyer Emily Dixon told me that, if a client shows her an exonerating photo or video, she isn’t expected to run analytic tests before submitting it into evidence. It’s reasonable to assume that a photo is real—for now. Yet we are fast approaching a world in which we can no longer believe our eyes or ears. The onset of artificial intelligence, in the justice system as elsewhere, is poised to overturn existing practices.

Specialists can still spot the anomalies that distinguish AI-generated images from real photos. “But in a year,” digital forensics expert Simon Lavallée told me, “we won’t.” Maura R. Grossman is a lawyer who has long worked to promote the use of advanced technologies for legal tasks, such as document review. When it comes to the threat of deepfakes, however, Grossman believes Canada’s evidence laws will require an overhaul. “Before, if I wanted to fake your signature, I had to have some talent,” she told me. “In this day and age, you could make a deepfake of my voice in two minutes.” Juries, Grossman has written, may increasingly be skeptical of all evidence.

For complainants like P, the erosion of this trust carries a high cost: left with only doubt, we may be tempted to rely on our instincts—indistinguishable from our desires, fears, and prejudices. In cases of domestic violence in particular, audio and visual evidence is a weighty counter to the social impulse to minimize. At work and with their friends, P says, her husband was funny and kind, but “he’s a very different person at home, to the point that most people wouldn’t believe you.”

Recently, the Law Commission of Ontario (LCO), an independent body that pushes for law reform, concluded a nationwide study of what is shaping up to be a head-on collision between two epistemic systems: the criminal justice system, which rests on the elimination of reasonable doubt, and artificial intelligence, a factory for doubt dissemination. “The risk of impacts on people’s lives is catastrophic,” Ryan Fritsch, the lawyer who headed the initiative, told me. The project brought together police officers, defence attorneys, prosecutors, judges, and human rights advocates, with the aim of formulating a set of recommendations to deliver to the Ontario government later this year.

The black mirror of deepfake evidence is not the only challenge the advent of artificial intelligence poses to the criminal justice system. Whether through the adoption of advanced analytics for risk prediction, the rise of predictive policing, or the use of large language models to summarize depositions or draft decisions, Canadian courts are about to grapple with a form of intelligence the mysterious workings of which chip away at the law’s foundation of transparency.

Internationally, Canadian lawmakers are already far behind in developing governance for the use of artificial intelligence within the justice system. Few guardrails are in place, and we are faced with clashing examples: Europe has taken a skeptical stance, sometimes outright banning the use of certain technologies, while the United States has leaned into decision making driven by complex algorithms and big data. Canada’s legal rules and procedures are designed for a pre-AI era. How will the public retain confidence in a system that rests on the painstaking articulation of reasoned logic as more and more of what happens in our courtrooms starts in a black box?

The attorney Rupert Ross used to work as a fishing guide, and in his book Dancing with a Ghost, he wrote about learning to predict lake conditions before leaving the shore. Standing at the edge of the dock, he would layer impressions of wind pattern, cloud cover, and temperature over his mental images of different spots on the water. It was as if each image were “a transparency of sorts, with all the variables sketched opaquely on its surface. Then similar images of past days at the same spot are slid under it.” If the feeling of the day contained a Proustian twinge of a previous day when he had found pickerel at a certain cove, he brought his angler clients to those waters.

Ross’s description reads like a paean to the subtleties of embodied memory, one of the quintessential characteristics that separates humans from machines. To the empirically minded, however,........

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