Top Podcasts on AI Ethics and Risks

“In other words, people who are actually experiencing a lot of the financial benefits of AI are not simultaneously experiencing job displacement. Now, cutting a little bit deeper here, economic benefits are definitely accruing to the more nimble. They write that those benefits skew heavily towards independent workers like entrepreneurs, small business owners, and even people with side projects.”

“If AI is as powerful as people say it's going to be, then there are going to be real-world reactions to that. And if we're going to analogize it to nuclear weapons, as Dario Amadei has done repeatedly, you have to think through what would happen in a world where a private company developed nuclear weapons. What would the government's response be? And that's not to say that the government response in that case is good or bad or does it follow sort of constitutional principles or whatever it might be.”

“It's inherently prone to all kinds of reasoning errors. It's inherently hard to control. I once called it a bull in a China shop. It's inherently prone to hallucinations, making stuff up. And that hasn't changed. I keep over and over hearing, oh, just give us more data. It will solve these problems. But the reality is, you know, as we're recording this, Gemini just came out and it hallucinates.”

“Navarro mentioned in an interview with Fox's Sunday Morning Futures that all these data center builders, from Meta on down, need to cover all the costs associated with the energy consumption of AI projects. This potential policy shift is a direct response to the massive investments big tech is making in artificial intelligence, with Meta alone planning to spend a jaw-dropping $135 billion on AI projects just this year.”

“The thing that AI introduces is that even with that growing problem, if I'm in the government And I say, I really want to know what Derek is doing... when the marginal cost of very, very, very sophisticated level attention falls to zero in the form of an artificial intelligence agent... all of a sudden it's like, well, wait. The calculus totally changes here.”

“David Autor at MIT offers a more nuanced view. His finding that 60% of current occupations didn't exist 80 years ago is genuinely grounds for optimism. New technology has always created categories of work that were unimaginable before the technology existed. But Autor draws a sharp distinction. AI could restore the middle class by enabling mid-skill workers to perform expert-level tasks, a nurse practitioner handling more complex diagnostics, a paralegal doing more sophisticated legal work, or it could destroy the middle class by simply replacing those workers entirely.”

“But if you have large language models integrated into this analytical apparatus, right, into the surveillance apparatus, you know, you could change the game entirely because now it's economic to look through all the messages. Now you could also do, if you wanted, semantic analysis of all the messages in a large database. You can piece together patterns of individuals, communities, or populations at large.”

“So it's, I mean, it's not really the military is using it like any new technology that they're going to try to find ways to be more effective, more efficient, much like these computers and computer software and computer networks today. So the military doesn't necessarily see this as something special or different, but really a productivity tool.”

“Children from birth will have an artificial intelligence as a companion that will learn them that will instruct them that will watch them and will report back one imagines to the boss man in Silicon Valley. And so you have AI as a tool and AI as a teacher, AI as a companion, AI as a creature with a consciousness of its own, more powerful, more intelligent, at least in the imagination of those pushing it, than any human being.”

“"The piece by Citrini's Alip Shah is called the 2028 Global Intelligence Crisis and walks through a doomsday scenario where effectively AI is so good that it's actually bearish, creating a doom spiral where AI does everything, allowing companies to cut human workers... Economics opinion writer Noah Smith wrote a response called the Citrini post is just a scary bedtime story. He summed it up, AI might take your job, but it probably won't crash the economy."”

“If we do end up in this world with powerful and pervasive AI, then when forced to choose between their AI provider and the Department of War, which constitutes a tiny fraction of the revenue, wouldn't they rather drop the government than the AI? Are we really racing to beat China and the CCP in AI just so we can adopt the most ghoulish parts of their system?”

“"You might ask why isn't this safety research happening at the very companies that are deploying this technology to billions of people as fast as humanly possible? And the answer is because they're not incentivized to do that. They're incentivized to get to artificial general intelligence as fast as possible. Whether you believe in artificial general intelligence or not, they're investors, and what they believe is that they can get there."”

“New technology doesn't just destroy jobs. It creates jobs that nobody could have anticipated. Now, am I saying everything is fine and nobody needs to worry? Absolutely not. There are real vulnerabilities. Entry-level roles look particularly exposed because they tend to involve narrower task bundles, those bundles we were talking about earlier, with fewer edge cases requiring human discretion. Back office and clerical work is clearly shrinking.”

“I think there are threats, particularly if we integrate these probabilistic generative and decision-making systems into high-stakes domains, nuclear, defense, energy, and put them to tasks that they are ultimately not secured or suited for. So you can have reward hacking, you can have emergent behavior, all of those things are real. Those aren't things that are simply going to sort of spring out of nowhere or Athena from Zeus's head and suddenly we have ephemeral technologies running around without our control or delegation in some sense.”

“Well, you're kind of seeing this with the AI race right now. You have to keep – these companies aren't building their own hardware, right? They're not building their own energy infrastructure. Like there's a lot of advanced stuff happening, but generally what they're doing is buying as many chips as they can, getting access to as much data as they can, and just training these models. And they're all using the same model architecture. And so these four or five top contenders end up with models that are like very, very, very close to each other.”