In this episode of GZERO AI, Taylor OwenOwen, host of the podcast “Machines Like Us,” explores how artificial intelligence is supercharging the stock market and transforming the economy. As AI propels the S&P 500 to new heights and dramatically boosts NVIDIA's stock price, researchers predict a future in which we'll be 1,000 times richer. But Owen raises an important question: is this rapid growth sustainable, or simply a bubble that will pop?
So, whatever skepticism you may have about the current AI boom, one thing cannot be denied: AI is accelerating the stock market and, more broadly, the economy.
The S&P 500 hit an all-time high this year, mainly thanks to AI. NVIDIA shares have risen 700% since the launch of ChatGPT, briefly becoming the world's most valuable company. And some researchers think it's about to get even worse. They argue that AI could lead to 30% per capita economic growth by 2100. This means that in 25 years of 30% per capita economic growth, we'll be 1,000 times wealthier than we are today.
But what are these bold predictions based on? It all comes down to whether human labor will be replaced by AI. These economists argue that AI can replace humans, that machines can do anything humans can't, or that humans can already do much better. But perhaps more importantly, humans will not be constrained by the number of humans in the workforce. They will be able to expand the workforce in ways that are not constrained by human capabilities. This, they argue, will fundamentally change the core dynamics of the economy.
But these are still predictions, wild speculations, often driven by those who benefit most from the hype around AI. At this point, there is no hard evidence that these things will necessarily come to fruition. And even if this wealth is created, 1,000 times more than we have today, there is no guarantee how it will be distributed, who will get it, who will benefit and who will not. What is clear is that, as in the past, wealth will likely trickle down to those who own and control these technologies. It is also clear that the most precarious people in the workforce are the most vulnerable and likely to suffer the most. If we are talking about machines replacing humans, then women and minorities, who are over-represented in the service workforce, will almost certainly be the ones to fall victim.
Some people argue that UBI might be the solution, that if we give this surplus wealth to everyone, they won't have to work. But there's a real problem here: people find meaning in work. I recently spoke to Rana Forouhar, an international economics reporter at the Financial Times, and she made the powerful argument to me that we get meaning from work, and taking that away would have serious political consequences. We're already starting to see those consequences. This is why Rana thinks we're in a bubble. She doesn't think the economy can be this good for this long. She argues that there's no precedent in history for it to last this long. But the story she claims about why the economy is growing is too weak to support the economic growth it's built on. For her, this is a clear sign that we're in a bubble. When you have a single story that doesn't allow for any contradictions, a clear story about a surefire path that's supporting a huge amount of economic activity, that's a sign of a bubble.
Finally, she argues that economic growth is too concentrated. Right now, too few people are benefiting from it. Most of the value created in AI is created by six or seven technology companies. This concentration is not good for society as a whole. But when the tech bubble bursts, we're all to blame. Like any bubble, we as a society, our pension funds, our investments, our retirement savings, the rest of the economy are at the mercy of this bubble. So we need to think really carefully about when and how this bubble deflates.
