Machines Like Us

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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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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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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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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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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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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“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:

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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.

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Towards the end of last year, Australia did something no other country had ever tried: it banned social media for kids under 16. And a bunch of others are following with similar laws, first Denmark, then France, then Indonesia and Austria. All in, there are now more than 25 countries that have either implemented, or are actively considering, social media bans for kids. It seems like Canada is moving there as well. In April, the Liberal party adopted a non-binding motion to restrict young people’s access to both social media and AI chatbots.

All over the world, you can hear parents breathing a sigh of relief. They’ve spent the last decade watching their kids become hooked on their devices, and now we’re doing something about it. It looks like we’re finally going to get our kids back.

But researchers like Candice Odgers are skeptical. Odgers is a psychology professor at UC Irvine who’s been studying the digital lives of young people for almost 20 years now, long before anyone was worried about what social media was doing to their brains. She says there isn’t really any research to suggest these bans will work. But her argument goes even deeper than that: she says the idea that smartphones have caused a youth mental health crisis just isn’t supported by the evidence.

So as governments all over the world start to kick kids off social media, and maybe even AI chatbots as well, Candice Odgers thinks we’re making a serious mistake. And I want to know if she’s right.

Machines Like Us is hosted by Taylor Owen, produced by Paradigms, and distributed by The Globe and Mail.

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The people running technology companies love to make wild predictions about the future. They’ve told us that artificial intelligence will cure cancer, eliminate drudgery and solve climate change. But those utopian visions have yet to materialize. Where are the revolutionary moonshots we’ve been promised?

Aza Raskin may well have one. Raskin is the president of the Center for Humane Technology and the co-founder of the Earth Species Project, a non-profit using machine learning to decode animal communication.

Raskin and his colleagues are envisioning a world where birds can vote and dolphins get to represent themselves in court. That might sound hard to believe – but Raskin says they’re not far from making it a reality.

So I wanted to ask him: what happens to our world – and to us – when animals have the right to speak?

My Octopus Teacher (2020), directed by Pippa Ehrlich & James Reed

Unlocking Avian Secrets: How Tiny Biologgers Are Revealing the Hidden Communication of Carrion Crows, by Earth Species Project

AI-powered playbacks engage in flexible vocal interactions with zebra finches, by Logan S. James et al.

Decoding Killer Whale Communication From Above and Below, by Earth Species Project

Innovative Behaviours and Synchronization in Bottlenose Dolphins, by Stacy Braslau-Schneck

What the World Thinks About AI and Animal Communication: Findings from Our First Global Survey, by Earth Species Project

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