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If we don’t build it, China will. That’s the rallying cry of the tech companies and governments racing to develop artificial intelligence as fast as humanly possible. The argument is that whoever reaches AGI first won’t just be dominant technologically, or economically – they’ll be the world’s next super power. But, if I’m being honest, I don’t know if that framing holds up. And part of the reason for that is that we don’t really understand China. Enter Keyu Jin. Jin is a Harvard trained economist who splits her time between London and Beijing, and her book, The New China Playbook, is her attempt to “read China in the original” – to provide a firsthand look at the forces that shaped the country’s unprecedented rise. China’s success is a puzzle. How did one of the poorest nations on the planet become the second richest in less than a century? How did an economy without free markets birth a tech sector that rivals – and in some ways surpasses – Silicon Valley? The answers to these questions aren’t academic. China became a global power without capitalism and without democracy, which means its success has profound implications for both. And as Canada sets out to find its footing in a rapidly changing world order, one thing is abundantly clear: we need to start reckoning with the Chinese playbook.  Mentions: The New China Playbook, by Keyu Jin Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Nine months ago, Elon Musk said 2025 would be the year chatbots became smarter than humans. Sam Altman thought it would be the year fully autonomous AIs entered the work force. And Dario Amodei, the CEO of Anthropic, predicted that by the end of the year, AI would be writing 90 per cent of all software code. We’re two weeks into the new year, and none of those things have happened. So, full disclosure: I have no idea if we’re going to reach artificial general intelligence or see the rise of humanoid robots this year. If the people at the centre of the industry can’t figure it out, I doubt I can. But I do have some ideas about how AI could reshape our world over the next 12 months. I think we’re going to see a new political movement pushing back against AI adoption and leaning into our collective humanity. Democratic governments will defy an increasingly protectionist America and start taking digital regulation seriously again. And we’ll start establishing cultural norms about AI use – like whether you really need to respond to that AI-generated e-mail your colleague just sent. On this episode, I turn the mics around and invite my longtime producer, Mitchell Stuart, to ask me about what’s actually in store for the year ahead. Mentioned: Trust, attitudes and use of artificial intelligence (2025), KPMG Human-centric AI: Perspectives on trust and the future of AI (2025), Telus Could an Alternative AI Save Us from a Bubble? (Gary Marcus), by Machines Like Us GPT-5 System Card, OpenAI Multi-model assurance analysis showing large language models are highly vulnerable to adversarial hallucination attacks during clinical decision support, by Mahmud Ohmar et al (Nature)  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jensen Huang is something of an enigma. The NVIDIA CEO doesn’t have social media and, until recently, rarely gave interviews. Yet he may be the most important person in AI. Under his leadership, NVIDIA has become a goliath. Somewhere between 80 and 90 per cent of AI tools run on NVIDIA hardware, making it the world’s most valuable company. But unlike his contemporaries, Huang has been remarkably quiet about the technology – and the world – he’s building. In his new book, The Thinking Machine: Jensen Huang, NVIDIA, and the World’s Most Coveted Microchip, journalist Stephen Witt pulls back the curtain. And what he finds is, at times, shocking: Huang believes there is zero risk in developing superintelligence. So who is Jensen Huang? And should we worry that the most powerful person in AI is racing forward at breakneck speed, blind to the potential consequences? Mentioned: The Thinking Machine: Jensen Huang, NVIDIA, and the World’s Most Coveted Microchip, by Stephen Witt How Jensen Huang’s Nvidia Is Powering the A.I. Revolution, by Stephen Witt (The New Yorker) The A.I. Prompt That Could End the World, by Stephen Witt (New York Times) Machines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at The Globe and Mail. Media sourced from the BBC. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

It was an idea that defied logic: an online encyclopedia that anyone could edit. You didn’t need to have a PhD or even use your real name – you just needed an internet connection. Against all odds, it worked. Today, billions of people use Wikipedia every month, and studies show it’s about as accurate as a traditional encyclopedia. But how? How did Wikipedia not just turn into yet another online cesspool, filled with falsehoods, partisanship and AI slop? Wikipedia founder Jimmy Wales just wrote a book called The Seven Rules of Trust, where he explains how he was able to build that rarest of things: a trustworthy source of information on the internet. In an era when trust in institutions is collapsing, Wales thinks he’s found a blueprint – not just for the web, but for everything else too. Mentioned: The Seven Rules of Trust by Jimmy Wales and Dan Gardner A False Wikipedia ‘Biography’ by John Seigenthaler (USA Today) Machines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at The Globe and Mail. Photo Illustration: The Globe and Mail/Brendan McDermid/Reuters Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Over the last couple of years, massive AI investment has largely kept the stock market afloat. Case in point: the so-called Magnificent 7 – tech companies like NVIDIA, Meta, and Microsoft – now account for more than a third of the S&P 500’s value. (Which means they likely represent a significant share of your investment portfolio or pension fund, too.) There’s little doubt we’re living through an AI economy. But many economists worry there may be trouble ahead. They see companies like OpenAI – valued at half a trillion dollars while losing billions every month – and fear the AI sector looks a lot like a bubble. Because right now, venture capitalists aren’t investing in sound business plans. They’re betting that one day, one of these companies will build artificial general intelligence. Gary Marcus is skeptical. He’s a professor emeritus at NYU, a bestselling author, and the founder of two AI companies – one of which was acquired by Uber. For more than two decades, he’s been arguing that large language models (LLMs) – the technology underpinning ChatGPT, Claude, and Gemini – just aren’t that good. Marcus believes that if we’re going to build artificial general intelligence, we need to ditch LLMs and go back to the drawing board. (He thinks something called “neurosymbolic AI” could be the way forward.) But if Marcus is right – if AI is a bubble and it’s about to pop – what happens to the economy then? Mentioned: The GenAI Divide: State of AI in Business 2025, by Project Nanda (MIT) MIT study finds AI can already replace 11.7% of U.S. workforce, by MacKenzie Sigalos (CNBC) The Algebraic Mind, by Gary Marcus We found what you’re asking ChatGPT about health. A doctor scored its answers, by Geoffrey A. Fowler (The Washington Post) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In Rutger Bregman’s first book, Utopia for Realists, the historian describes a rosy vision of the future – one with 15-hour work weeks, universal basic income and massive wealth redistribution. It’s a vision that, in the age of artificial intelligence, now seems increasingly possible. But utopia is far from guaranteed. Many experts predict that AI will also lead to mass job loss, the development of new bioweapons and, potentially, the extinction of our species. So if you’re building a technology that could either save the world or destroy it – is that a moral pursuit? These kinds of thorny questions are at the heart of Bregman’s latest book, Moral Ambition. In a sweeping conversation that takes us from the invention of the birth control pill to the British Abolitionist movement, Bregman and I discuss what a good life looks like (spoiler: he thinks the death of work might not be such a bad thing) – and whether AI can help get us there. Mentioned:  Moral Ambition, by Rutger Bregman Utopia for Realists, by Rutger Bregman  If Anyone Builds It, Everyone Dies: The Case Against Superintelligent AI, by Eliezer Yudkowsky and Nate Soares Machines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at The Globe and Mail. Support for Machines Like Us is provided by CIFAR and the Max Bell School of Public Policy at McGill University. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

At Donald Trump’s inauguration earlier this year, the returning president made a striking break from tradition. The seats closest to the president – typically reserved for family – went instead to the most powerful tech CEOs in the world: Elon Musk, Mark Zuckerberg, Jeff Bezos and Sundar Pichai. Between them, these men run some of the most profitable companies in history. And over the past two decades, they’ve used that wealth to reshape our public sphere. But this felt different. This wasn’t discreet backdoor lobbying or a furtive effort to curry favour with an incoming administration. These were some of the most influential men in the world quite literally aligning themselves with the world’s most powerful politician – and his increasingly illiberal ideology. Carole Cadwalladr has been tracking the collision of technology and politics for years. She’s the investigative journalist who broke the Cambridge Analytica story, exposing how Facebook data may have been used to manipulate elections. Now, she’s arguing that what we’re witnessing goes beyond monopoly power or even traditional oligarchy. She calls it techno-authoritarianism – a fusion of Trump’s authoritarian political project with the technological might of Silicon Valley. So I wanted to have her on to make the case for why she believes Big Tech isn’t just complicit in authoritarianism, but is actively enabling it. Mentioned: The First Great Disruption 2016-2024, by Carole Cadwalladr Trump Taps Palantir to Compile Data on Americans, by Sheera Frenkel and Aaron Krolik (New York Times) This is What a Digital Coup Looks Like, by Carole Cadwalladr (TED) The Nerve News Machines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at The Globe and Mail. Support for Machines Like Us is provided by CIFAR and the Max Bell School of Public Policy at McGill University. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

AI art is everywhere now. According to the music streaming platform Deezer, 18 per cent of the songs being uploaded to the site are AI-generated. Some of this stuff is genuinely cool and original – the kind of work that makes you rethink what art is, or what it could become. But there are also songs that sound like Drake, cartoons that look like The Simpsons, and stories that read like Game of Thrones. In other words, AI-generated work that’s clearly riffing on – or outright mimicking – other people’s art. Art that, in most of the world, is protected by copyright law. Which raises an obvious question: how is any of this legal? The AI companies claim they’re allowed to train their models on this work without paying for it, thanks to the “fair use” exception in American copyright law. But Ed Newton Rex has a different view: he says it’s theft. Newton Rex is a classical music composer who spent the better part of a decade building an AI music generator for a company called Stability AI. But when he realized the company – and most of the AI industry – didn’t intend to license the work they were training their models on, he quit. He has been on a mission to get the industry to fairly compensate creators ever since. I invited him on the show to explain why he believes this is theft at an industrial scale – and what it means for the human experience when most of our art isn’t made by humans anymore, but by machines. Mentioned: Copyright and Artificial Intelligence: Generative AI Training, by the United States Copyright Office A.I. Is Coming for Culture, by Josha Rothman (The New Yorker) Machines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Host direction by Athena Karkanis. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at The Globe and Mail. Media sourced from BBC News. Support for Machines Like Us is provided by CIFAR and the Max Bell School of Public Policy at McGill University. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The story of how Geoffrey Hinton became “the godfather of AI” has reached mythic status in the tech world. While he was at the University of Toronto, Hinton pioneered the neural network research that would become the backbone of modern AI. (One of his students, Ilya Sutskever, went on to be one of OpenAI’s most influential scientific minds.) In 2013, Hinton left the academy and went to work for Google, eventually winning both a Turing Award and a Nobel Prize. I think it’s fair to say that artificial intelligence as we know it, may not exist without Geoffrey Hinton. But Hinton may be even more famous for what he did next. In 2023, he left Google and began a campaign to convince governments, corporations and citizens that his life’s work – this thing he helped build – might lead to our collective extinction. And that moment may be closer than we think, because Hinton believes AI may already be conscious. But even though his warnings are getting more dire by the day, the AI industry is only getting bigger, and most governments, including Canada’s, seem reluctant to get in the way. So I wanted to ask Hinton: If we keep going down this path, what will become of us? Mentioned: If Anyone Builds It, Everyone Dies: The Case Against Superintelligent AI, by Eliezer Yudkowsky and Nate Soares Agentic Misalignment: How LLMs could be insider threats, by Anthropic Machines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at The Globe and Mail. Support for Machines Like Us is provided by CIFAR and the Max Bell School of Public Policy at McGill University. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Just two months after ChatGPT was launched in 2022, a survey found that 90 per cent of college students were already using it. I’d be shocked if that number wasn’t closer to 100 per cent by now. Students aren’t just using artificial intelligence to write their essays. They’re using it to generate ideas, conduct research, and summarize their readings. In other words: they’re using it to think for them. Or, as New York Magazine recently put it: “everyone is cheating their way through college.” University administrators seem paralyzed in the face of this. Some worry that if we ban tools like ChatGPT, we may leave students unprepared for a world where everyone is already using them. But others think that if we go all in on AI, we could end up with a generation capable of producing work – but not necessarily original thought. I’m honestly not sure which camp I fall into, so I wanted to talk to two people with very different perspectives on this. Conor Grennan is the Chief AI Architect at NYU’s Stern School of Business, where he’s helping students and educators embrace AI. And Niall Ferguson is a senior fellow at Stanford and Harvard, and the co-founder of the University of Austin. Lately, he’s been making the opposite argument: that if universities are to survive, they largely need to ban AI from the classroom. Whichever path we take, the consequences will be profound. Because this isn’t just about how we teach and how we learn – it’s about the future of how we think. Mentioned: AI’s great brain robbery – and how universities can fight back, by Niall Ferguson (The London Times) Everyone Is Cheating Their Way Through College, by James D. Walsh (New York Magazine) Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task, by Nataliya Kos’myna (MIT Media Lab) The Diamond Age, by Neal Stephenson How the Enlightenment Ends, by Henry A. Kissinger Machines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Host direction by Athena Karkanis. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at the Globe & Mail. Support for Machines Like Us is provided by CIFAR and the Max Bell School of Public Policy at McGill University. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In the chaotic early months of his second term, Donald Trump has attacked the Canadian economy and mused about turning Canada into the “51st state.” Now, after decades of close allyship with the U.S., our relationship with America has suddenly become fraught. Which means that Canadians are now starting to ask what a more sovereign Canada might look like – a question Jim Balsillie has been thinking about for 30 years. Balsillie is the former co-CEO of Research in Motion, the company that developed the Blackberry, and is one of the most successful business people in Canada. He’s also one of the patriotic, which makes his recent criticism of our country that much more meaningful. As Balsillie has pointed out, our GDP per capita is currently about 70% of what it is in the U.S., our productivity growth has been abysmal for years, and our high cost of living means that 1 in 4 Canadians are now food insecure. But, according to Balsillie, none of this can be blamed on Trump. He thinks that over the last thirty years we’ve clung to an outdated economic model and have allowed our politics to be captured by corporate interests. So, with less than a week to go before the federal election, I thought it was the perfect time to sit down with Jim and ask him how we might build a stronger, more sovereign Canada. Mentioned: “Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS),” The World Trade Organization “Reinforcing Canada’s security and sovereignty in the Arctic,” Prime Minister of Canada “Ontario Welcomes Siemens’ $150 Million Investment to Establish New Technology Centre in Oakville,” news release from the Government of Ontario Further Reading: “We are all economic nationalists now,” by Jim Balsillie (National Post) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

We’re a few weeks into a federal election that is currently too close to call. And while most Canadians are wondering who our next Prime Minister will be, my guests today are preoccupied with a different question: will this election be free and fair? In her recent report on foreign interference, Justice Marie-Josée Hogue wrote that “information manipulation poses the single biggest risk to our democracy”. Meanwhile, senior Canadian intelligence officials are predicting that India, China, Pakistan and Russia will all attempt to influence the outcome of this election. To try and get a sense of what we’re up against, I wanted to get two different perspectives on this. My colleague Aengus Bridgman is the Director of the Media Ecosystem Observatory, a project that we run together at McGill University, and Nina Jankocwicz is the co-founder and CEO of the American Sunlight Project. Together, they are two of the leading authorities on the problem of information manipulation. Mentioned: “Public Inquiry Into Foreign Interference in Federal Electoral Processes and Democratic Institutions,” by the Honourable Marie-Josée Hogue "A Pro-Russia Content Network Foreshadows the Automated Future of Info Ops,” by the American Sunlight Project Further Reading: “Report ties Romanian liberals to TikTok campaign that fueled pro-Russia candidate,” by Victor Goury-Laffont (Politico) “2025 Federal Election Monitoring and Response,” by the Canadian Digital Media Research Network “Election threats watchdog detects Beijing effort to influence Chinese Canadians on Carney,” by Steven Chase (Globe & Mail) “The revelations and events that led to the foreign-interference inquiry,” by Steven Chase and Robert Fife (Globe & Mail) “Foreign interference inquiry finds ‘problematic’ conduct,” by The Decibel Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

If you’re having a conversation about the state of journalism, it’s bound to get a little depressing.  Since 2008, more than 250 local news outlets have closed down in Canada. The U.S. has lost a third of the newspapers they had in 2005. But this is about more than a failing business model. Only 31 percent of Americans say they trust the media. In Canada, that number is a little bit better – but only a little.  The problem is not just that people are losing their faith in journalism. It’s that they’re starting to place their trust in other, often more dubious sources of information: TikTok influencers, Elon Musk’s X feed, and The Joe Rogan Experience.  The impact of this shift can be seen almost everywhere you look. 15 percent of Americans believe climate change is a hoax. 30 percent believe the 2020 election was stolen. 10 percent believe the earth is flat.  A lot of this can be blamed on social media, which crippled journalism's business model and led to a flourishing of false information online. But not all of it. People like Jay Rosen have long argued that journalists themselves are at least partly responsible for the post-truth moment we now find ourselves in.  Rosen is a professor of journalism at NYU who’s been studying, critiquing, and really shaping, the press for nearly 40 years. He joined me a couple of weeks ago at the Attention conference in Montreal to explain how we got to this place – and where we might go from here.  A note: we recorded this interview before the Canadian election was called, so we don’t touch on it here. But over the course of the next month, the integrity of our information ecosystem will face an inordinate amount of stress, and conversations like this one will be more important than ever.    Mentioned: "Digital News Report Canada 2024 Data: An Overview," by Colette Brin, Sébastien Charlton, Rémi Palisser, Florence Marquis  "America’s News Influencers,"  by Galen Stocking, Luxuan Wang, Michael Lipka, Katerina Eva Matsa,Regina Widjaya,Emily Tomasik andJacob Liedke Further Reading:  "Challenges of Journalist Verification in the Digital Age on Society: A Thematic Review," Melinda Baharom, Akmar Hayati Ahmad Ghazali, Abdul Muati, Zamri Ahmad "Making Newsworthy News: The Integral Role of Creativity and Verification in the Human Information Behavior that Drives News Story Creation," Marisela Gutierrez Lopez, Stephann Makri, Andrew MacFarlane, Colin Porlezza, Glenda Cooper, Sondess Missaoui "The Trump Administration and the Media (2020)," by Leonard Downie Jr. for the Committee to Protect Journalists. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

When the American company OpenAI released ChatGPT, it was the first time that a lot of people had ever interacted with Generative AI. ChatGPT has become so popular that, for many, it’s now synonymous with artificial intelligence. But that may be changing. Earlier this year a Chinese startup called DeepSeek launched its own AI chatbot, sending shockwaves across Silicon Valley. According to DeepSeek, their model – DeepSeek-R1 – is just as powerful as ChatGPT but was developed at a fraction of the cost. In other words, this isn’t just a new company, it could be an entirely different approach to building artificial intelligence. To try and understand what DeepSeek means for the future of AI, and for American innovation, I wanted to speak with Karen Hao. Hao was the first reporter to ever write a profile on OpenAI and has covered AI for The MIT Tech Review, The Atlantic and the Wall Street Journal. So she’s better positioned than almost anyone to try and make sense of this seemingly monumental shift in the landscape of artificial intelligence. Mentioned: “The messy, secretive reality behind OpenAI’s bid to save the world,” by Karen Hao Further Reading: “DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning,” by DeepSeek-AI and others. “A Comparison of DeepSeek and Other LLMs,” by Tianchen Gao, Jiashun Jin, Zheng Tracy Ke, Gabriel Moryoussef “Technical Report: Analyzing DeepSeek-R1′s Impact on AI Development,” by Azizi Othman Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Do I have your attention right now? I’m guessing probably not. Or, at least, not all of it. In all likelihood, you’re listening to this on your morning commute, or while you wash the dishes or check your e-mail. We are living in a world of perpetual distraction. There are more things to read, watch and listen to than ever before – but our brains, it turns out, can only absorb so much. Politicians like Donald Trump have figured out how to exploit this dynamic. If you’re constantly saying outrageous things, it becomes almost impossible to focus on the things that really matter. Trump’s former strategist Steve Bannon called this strategy “flooding the zone.” As the host of the MSNBC show All In, Chris Hayes has had a front-row seat to the war for our attention – and, now, he’s decided to sound the alarm with a new book called The Sirens’ Call: How Attention Became the World’s Most Endangered Resource. Hayes joined me to explain how our attention became so scarce, and what happens to us when we lose the ability to focus on the things that matter most. Mentioned: "Twitter and Tear Gas: The Power and Fragility of Networked Protest," by Zeynep Tufekci Further Reading: "Ethics of the Attention Economy: The Problem of Social Media Addiction," by Vikram R. Bhargava and Manuel Velasquez. "The Attention Economy Labour, Time and Power in Cognitive Capitalism," by Claudio Celis Bueno “The business of news in the attention economy: Audience labor and MediaNews Group’s efforts to capitalize on news consumption,” Brice Nixon Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.