The study of economic growth is a modern phenomenon. In fact, economists didn’t get serious about measuring it until the mid-20th century. So what brought growth into focus and are the ways we measure it today adequate for a technologically-advanced world?
Daniel Susskind is an economics professor at King's College London and a senior research associate at the Institute for Ethics in AI at Oxford University. His books like The Future of the Professions: How Technology Will Transform the Work of Human Experts and Growth: A History and a Reckoning explore the impact of technology on work and the economy.
Daniel and Greg discuss the history and circumstances that led to the creation of the GDP and its modern limitations, the moral and environmental challenges associated with a relentless pursuit of growth, and the need for societies to rethink the meaning and value of work in an increasingly automated world.
*unSILOed Podcast is produced by University FM.*
Episode Quotes:
The modern economic thought about the origins of growth
10:22: Growth doesn't come from the material world. It doesn't come from the world of tangible objects, but it comes from the intangible world of ideas. And ideas have all these interesting properties: they're nonrival, they're nonexcludable. But the key point is that whereas the world of finite material resources is finite, there's only so much material stuff out there. The world of ideas is unimaginably vast, for all intents and purposes, as good as infinite. And so if growth comes not from using more and more finite resources, but from discovering new ideas about how we can make ever more productive use of those finite resources, then the kind of constraints, the bottlenecks to growth, aren't to be found in the material world of those finite resources but it's to be found in our inability to discover enough new ideas about the world.
What do we do about growth?
11:23: If we want more growth, we need to become societies that discover new and more interesting ideas about how we can use the resources that we have.
Two big problems when it comes to GDP measure
14:40: One is technical failings, which is that it's meant to be a measure of the activity that takes place in the market, and it's not a particularly good measure. Many of the things that we use today are free. Think about the search engines we use, the sort of email browsers, and so on, the sort of first generation of generative AI systems, whatever it might be; we don't pay a price for them in the market. And so they're not captured by traditional GDP statistics. The other thing, of course, that GDP is very bad at capturing is quality improvements. And if you think about particular technologies that we use, something like an iPhone today might have the same price as an iPhone X many years ago. All the different dimensions on which the quality of that technology has improved just aren't captured.
On the relationship between work and meaning
56:38: Although people say there's a strong relationship between work and meaning, actually, there's a lot of heterogeneity. Actually, a lot of people do not get meaning from their work. If they could get an income without working, they would. And you can see this in the simple polls that are done. Lots of people do not get meaning and purpose from their work. They don't think they're making a meaningful contribution to the world. I think it's often the people who write about this stuff are sometimes confusing the meaning that they get from their work as a kind of generalizable insight. I just don't think it's true.
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