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Toronto police turned to AI in Sherman murder case. So I did too

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Artificial Intelligence (AI) has dramatically changed the landscape of numerous industries. One of the areas where its impact is being increasingly felt is in criminal investigations. The Toronto police, in their ongoing investigation into the unsolved murders of billionaires Barry and Honey Sherman, have turned to AI for assistance in analyzing thousands of pages of partially unsealed documents. As a reporter following the case, I found myself intrigued by the police’s innovative approach. Consequently, I decided to try it out for myself. “Toronto police turned to AI in Sherman murder case. So I did too.”

A Glimpse into the AI Experience

The AI tool I used for my investigation is a Google product called Gemini AI. I uploaded almost 4,000 pages of partially unsealed police documents, containing witness statements, and police theories. While I was initially skeptical, my experience with Gemini gave me an insight into how AI can extract crucial information hidden in a sea of data. This was evident when the AI tool provided me with a piece of information I had been seeking: the timeline of the “walking man” who is considered a prime suspect in the Sherman case.

AI’s Hallucination: A Word of Caution

Although Gemini was able to provide some useful information, the process was not without its flaws. The AI tool initially provided a specific timeframe for the “walking man”, suggesting he was caught on camera near the Sherman house on the night of the murders. However, upon further probing, Gemini admitted that it had “hallucinated” the information. This incident serves as a cautionary tale of AI’s tendency to “please the user” by making predictive guesses, which are not always accurate.

The Role of AI in Criminal Investigations

The Toronto Police Service’s AI policy requires a “human in the loop,” ensuring that any decision or classification made by the technology must be confirmed by a qualified human. As more police services turn to AI technology, there’s a growing concern that the technology, while helpful in solving crimes, also carries significant risks of violating rights, perpetuating bias, and eroding public trust in the justice system.

Unsolved Case: The Sherman Murders

The Sherman case remains unsolved eight years on. The victims, Barry and Honey Sherman, were found strangled in their home in December 2017. The Toronto police are investigating several “persons of interest”, but the prime suspect remains the unidentified “walking man” caught on camera near the Sherman house on the night of the murders. Despite the passage of time, the Toronto police maintain that the case is not cold and continue their efforts to solve the tragic double murder.

AI and Future Investigations

My experience with Gemini AI in investigating the Sherman case has given me a glimpse into the potential and limitations of AI in criminal investigations. While AI can be a powerful tool in extracting and analyzing information, it’s crucial to approach its assistance with caution, understanding its propensity for “hallucination”. As technology continues to advance, the role of AI in criminal investigations is likely to become even more significant, but it should never replace human intuition, experience, and judgment.

author avatar
Ethan Radcliffe
Ethan Radcliffe is a senior reporter and digital editor at The Toronto Insider, specializing in Canadian federal policy, GTA urban development, and national economic trends. With over a decade of experience in North American journalism, Ethan focuses on translating complex legislative and economic developments into clear, accessible reporting for Canadian readers. Ethan’s work emphasizes policy analysis, government accountability, and data-driven reporting, with a strong focus on how federal and provincial decisions impact communities across the Greater Toronto Area and beyond. He has covered infrastructure planning, housing policy, fiscal strategy, and regulatory changes affecting Canadian households and businesses. A graduate of Toronto Metropolitan University’s School of Journalism, Ethan brings expertise in investigative reporting, long-form analysis, editorial standards, and digital publishing best practices. His reporting is guided by verifiable sources, public records, and transparent sourcing. In addition to reporting, Ethan has experience in newsroom editing, fact-checking workflows, SEO-informed journalism, and audience analytics, ensuring stories meet both editorial integrity standards and modern digital discoverability requirements. Ethan is committed to objective, fact-driven journalism and adheres to established ethical guidelines, prioritizing accuracy, clarity, and public trust in all reporting.

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