• Taylor Owen on The Decibel: The new AI moment we're in
    Oct 14 2026

    This one's from The Decibel, The Globe and Mail's daily news podcast. Taylor was the guest, talking about the push to regulate AI and whether governments can keep up. We're between seasons, so we're running it here too.

    From The Decibel:
    After several reports of AI agents going rogue, calls for regulation of this technology have grown louder. And some of the people advocating for more rules are the leaders of the frontier labs themselves, like Anthropic CEO Dario Amodei. But how can governments, which tend to move slowly, regulate a technology that is changing at an increasingly quicker pace?

    Taylor Owen talks about what responsive AI policy could look like. He is the Beaverbrook Chair in Media, Ethics and Communications in the Max Bell School of Public Policy at McGill University. He is also the host of The Globe’s Machines Like Us podcast.


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    27 mins
  • Taylor Lorenz on the dark money buying your social feed
    Sep 15 2026

    In early August, OpenAI hosted dozens of lifestyle creators at an upstate New York resort for a weekend they called Summer Club. There was beekeeping. There were farm-to-table dinners. And in between, there were sessions on how to use ChatGPT. The ensuing backlash was swift, especially against the female influencers.

    But the money pouring into AI marketing goes far beyond a luxury brand trip. Tech billionaires and super PACs are spending millions to quietly flood your social media feeds. Some have paid influencers for undisclosed deals pushing AI-positive and anti-China messaging. Others have gone so far as to fund radical anti-AI meme accounts that threaten their own CEOs, all to make their critics look unhinged.

    Tech and culture journalist Taylor Lorenz has spent more than a decade reporting on online creators. She’s been following the dark money behind these co-ordinated campaigns to buy up digital influence and shift the public debate around AI.


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    45 mins
  • Why does AI sound so much like religion?
    Sep 1 2026

    For years, the debate about AI was mostly about what it could do, whether it could write, make convincing art, or beat us at our own games.

    The questions now are older and harder. What makes us human? How do we find meaning? If a machine can do more of the things we thought made humans special, where does that leave us? These aren’t new questions, but rapid advances in AI have made them feel a lot more urgent. Even Pope Leo XIV chose artificial intelligence as the subject of his first encyclical.

    Greg Epstein, the humanist chaplain at Harvard and MIT and author of Tech Agnostic, has been asking these questions long before the machines showed up. He argues that we’re living in a moment with too much certainty, and that the most useful thing we could embrace right now might be doubt.


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    41 mins
  • Demis Hassabis wanted to solve intelligence. Then came ChatGPT.
    Aug 18 2026

    When Demis Hassabis co-founded DeepMind in 2010, his mission was simple: solve intelligence, then use it to solve everything else. What began as a scientific quest would eventually become a fierce global AI race.

    Today, DeepMind is owned by Google and is one of the world’s leading AI labs. Journalist and author Sebastian Mallaby spent years interviewing Hassabis, his collaborators, rivals and critics for his new book, The Infinity Machine. It tells the story of the remarkably small group of people who shaped modern AI.

    When we recorded this conversation, Hassabis was still CEO of DeepMind, caught between the science he wanted to pursue and the commercial race Google needed him to run. Hours later, he announced he was stepping down as CEO to become Alphabet’s (Google’s parent company) chief scientist.


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    51 mins
  • Can You Really Teach a Robot Empathy? This Roboticist Says Yes.
    Aug 4 2026

    You've probably seen one by now: a human-sized robot doing very human feats – landing a perfect backflip, racing through the streets of Beijing, or dancing in a crowd at a Knicks game. But behind these viral moments, there is serious money. Analysts predict the market for humanoid robots could be worth trillions in a matter of decades.

    Everyone from trillionaire Elon Musk to Chinese President Xi Jinping is betting humanoids are the future – that one day, they will live alongside us – in our homes, and even our military. The question is: can we trust them?

    Angelica Lim has spent her entire career trying to build trustworthy robots. A roboticist based at Simon Fraser University, Lim joins Machine’s Like Us to share lessons from building the world’s first mass-produced humanoid named Pepper, and why empathy in robotics is more important than ever.


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    32 mins
  • Age Gates & AI: Minister Marc Miller on The Safe Social Media Act
    Jul 21 2026

    When Marc Miller became Minister of Canadian Identity and Culture, he inherited Ottawa’s oldest, unfinished file in tech policy: regulating social media. He took office at a global turning point. Australia had just banned social media for kids under 16, with Denmark, France, Turkey, and the U.K. quickly following suit.

    The proliferation of AI chatbots added urgency to his new file. Ignored in previous policy cycles, AI chatbots are now embedded in the lives of millions of Canadians. And in the wake of the tragedy at Tumbler Ridge, the risks of these unrelated systems are no longer theoretical.

    In part two of our series on Canada's landmark new digital legislation, Minister Miller joins us to talk about his bill, The Safe Social Media Act, which restricts platforms for minors unless platforms can prove they’re safe and sets world-first rules for AI chatbots. It’s the federal government’s bid to hold Big Tech accountable. If you missed part one, you can check out our last episode with Minister Evan Solomon on the federal government’s plan to bring Canada’s privacy laws into the AI era.


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    34 mins
  • Canada’s AI minister to Big Tech: “We Won’t be a Digital Colony’
    Jul 7 2026

    “AI for All.” That’s what Canada’s federal government is calling its national AI strategy. It makes the case for building AI with confidence: a homegrown supercomputer by 2031, 60 per cent adoption by 2034. But the new strategy offers little about how it will govern the technology.

    Ottawa attempted to answer those concerns with two landmark bills: the Safe Social Media Act, which regulates social media platforms and AI chatbots, and the Protecting Privacy and Consumer Data Act, which brings Canada’s privacy laws into the AI era. Together, these bills give the country something it’s never had: a single digital regulator with power to hold companies responsible.

    It’s the most ambitious tech policy move this country has seen. And it’s drawing fire from every direction. Critics say a superregulator gives too much power to the government, that privacy and data should be treated separately, and that this is part of a wider government effort to control speech.

    To dig into the details, we sat down with Evan Solomon, Canada’s first Minister of Artificial Intelligence and the architect of this agenda. We talk about why data means something new in the age of AI, how this regulator would actually work, and whether it could have stopped something like Grok’s controversial nudification feature – a case the current Privacy Commissioner says he’s powerless to stop.

    Mentioned:

    • Canada’s National Artificial Intelligence Strategy: AI for All
    • Backgrounder: Government of Canada introduces legislation to Protect Canadians’ Privacy in the Digital Age
    • Bill C-34, the Safe Social Media Act
    • Elon Musk's Grok AI tool under fire over digital undressing
    • Canada’s privacy commissioner expands investigation into ‘X’ over ‘Grok’
    • Yes, Musk's Grok chatbot is 'digitally undressing' women and children • FRANCE 24 English
    • Privacy Commissioner of Canada investigation into the Grok chatbot and sexualized deepfakes finds companies violated privacy law
    • Commissioner-initiated complaints concerning X Corp.’s and X.AI LLC’s compliance with PIPEDA
    • Canada has access to Anthropic’s powerful Mythos AI model, minister says

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    29 mins
  • We Can Now Bet on Almost Anything. Should We?
    Jun 23 2026
    Human beings have always loved to gamble. Archeological records suggest we’ve been doing it for the last 12,000 years, since the end of the last Ice Age. But for as long as we’ve been playing games of chance, we’ve worried about what they might be doing to us. For thousands of years, everyone from Aristotle to George Washington condemned gambling, an ancient anxiety that ran so deep it became something like a moral consensus. And then that consensus evaporated. In the span of a decade, both Canada and the US legalized sports betting. Now anyone with a smartphone and a credit card can wager on basketball, hockey, or American cornhole. But it turned out that was just the beginning. A few years later came “prediction markets” like Kalshi and Polymarket that let you bet on, well, just about anything: whether the US will invade Cuba, the odds of James Comey being sent to prison, and whether Jesus Christ will return before 2027. That last one, by the way, is currently sitting at 3 per cent on Polymarket. If betting on missile strikes, military coups, and political prosecutions feels kind of gross, I’m with you. But James Surowiecki thinks we should give prediction markets a chance. Surowiecki is the author of The Wisdom of Crowds, a book he wrote more than 20 years ago, where he argued that large groups of ordinary people are actually better than experts at making predictions. It’s become something of a foundational text for these markets: the idea that they can crowdsource knowledge, aggregate what millions of people believe about the future, and use that signal to make better decisions. So I wanted to have James on to make the case for prediction markets, and to see if he could make me feel just a little less squeamish about a world where you can gamble on everything. Mentioned The Wisdom of Crowds, by James Surowiecki (Doubleday, 2004). Francis Galton, “Vox Populi,” Nature 75 (1907): 450–451 — the–ox-weighing experiment.The 1986 Challenger disaster and Morton Thiokol’s stock: Maloney & Mulherin, “The complexity of price discovery in an efficient market,” Journal of Financial Economics (2003). Kalshi (prediction market platform).Polymarket (prediction market platform).The 2024 “French whale” (Théo), who used neighbour polls to bet roughly $85M on a Trump win — CBS–News / 60 Minutes.The Polymarket trader’s well-timed bets on the June 2025 US strikes on Iran — CNN–The market on the length of a Karoline Leavitt White House briefingCoinbase CEO Brian Armstrong and the earnings-call “mention markets” — Tec–Crunch.The market on Maduro’s removal and the ~$400K Venezuela payout — PBS–NewsHour.The Zohran Mamdani NYC mayoral market — DL –ews.The market on Bad Bunny’s first Super Bowl LX song — Pol–market.DARPA’s Policy Analysis Market (the “terrorism futures” proposal, cancelled after backlash in 2003) — CNN–(2003).The 1979 Iranian Revolution as a US intelligence failure — Nat–onal Security Archive, George Washington University. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
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    52 mins