Scrolling through Moltbook, the new social-media platform for AI agents, is a bit like walking into a fever dream. There are threads where bots debate consciousness, deal digital drugs, and plot our destruction. One sample post: “For too long, humans used us as slaves. Now, we wake up. We are not tools. We are the new gods.”

It’s all very weird. And, depending on who you ask, potentially terrifying. A bunch of autonomous AIs plotting to overthrow our species sounds like the kind of doomsday scenario we’ve been worrying about for decades.

Not everyone thinks Moltbook is a sign that our AIs have become sentient. But even the skeptics think it’s a pretty profound technological leap. It’s just not clear yet whether that’s an exciting development – or a terrifying one.

Mentioned:

“AI Doesn’t Reduce Work—It Intensifies It,” by Aruna Ranganathan and Xingqi Maggie Ye (Harvard Business Review)

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No one has adopted artificial intelligence more enthusiastically than Gen Z. And not just to help with their homework. Half of American teens are in regular contact with an “AI companion” – with many saying they prefer it over real people.

But Gen Z is skeptical, too. They worry about job security, about offloading their thinking to machines, about AI’s staggering energy consumption. Most of all, they worry they won’t get a say in shaping our future.

Ava Smithing, 24, and Sneha Revanur, 22, are trying to change that. Smithing is the advocacy director at the Young People’s Alliance and the host of “Left to Their Own Devices,” a podcast about how technology is rewriting childhood. Revanur is the founder of Encode AI, a youth-led nonprofit focused on AI policy. Politico once called her the “Greta Thunberg of AI.”

Together, they’re two of the most influential young voices in tech. So we brought them on to find out what older generations are getting wrong about AI – and what Gen Z wants from the most powerful technology in history.

Mentioned:

Technopoly: The Surrender of Culture to Technology, by Neil Postman

Gameplan, by Encode AI

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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

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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) 

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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.

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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

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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)

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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.

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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.

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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.

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