AI and the Looming Economic Challenge

Today on the AI Daily Brief AI and Our Looming Economic Challenge the AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. To join the conversation, follow the Discord link in our show Notes. Hello friends.

Happy weekend.

And it being the weekend, of course, that means it's time for a Long Reads episode. Now we have an interesting one today. It is an essay in the New York Times from MIT professor Darren Acemoglu, who, among other credits, recently received the Nobel Prize for Economic Science this year. Now, as you will see, Acemoglu has a different perspective on how fast and how thoroughly AI is going to be adopted than I and perhaps many of you do. He is sometimes touted as an AI skeptic, although I tend to think he's a lot more nuanced than that. Still, this is an essay that gets much broader than AI and puts it in a larger context, and I think it's really valuable in that light.

So what we're going to do is.

To turn it over to 11 labs me to read this essay and then I will be back with a few.

Of my own thoughts America is sleepwalking into an economic storm. Inflation seems under control. The job market remains healthy. Wages, including at the bottom end of the scale, are rising. But this is just a lull. There is a storm approaching and Americans are not prepared. Barreling toward us are three epochal changes poised to reshape the US Economy in coming an aging population, the rise of artificial intelligence, and the rewiring of the global economy. There should be little surprise in this, since all these are evolving slowly, in plain sight. What has not been fully understood is how these changes in combination are likely to transform the lives of working people in ways not seen since the late 1970s, when wage inequality surged and wages at the low end stagnated or even fell together. If handled correctly, these challenges could remake work and deliver much higher productivity, wages and opportunities, something the computer revolution promised and never fulfilled. If we mismanage the moment, they could make good, well paying jobs scarcer and the economy less dynamic. Our decisions over the next five to 10 years will determine which path we take. Our dysfunctional political system, which is increasingly short termist in its vision for the country, is unlikely to prepare us for these changes. Neither Vice President Kamala Harris nor former President Donald Trump is focusing on them with any seriousness in their election campaigns. Nor do we see comprehensive plans from either party to make the investments necessary to equip the American workforce to deal with the coming challenges. The US workforce has never aged like this. In 2000, there were about 27Americans above the age of 65 for every 100Americans of prime working age between the ages of 20 and 49. By 2020, this number had increased to 39. By 2040, it will have risen to 54. Because these changes are driven mostly by a decline in fertility, the US Workforce will also soon begin to grow more slowly if immigration into the United States is reduced, as seems likely no matter who wins the election, this will only contribute to the aging problem. Many jobs in the economy, such as in manufacturing and construction, require physical strength and stamina, which start declining as an individual ages. Even with the kinds of health improvements we've seen, workers typically reach peak productivity in their 40s. The young are also more entrepreneurial and willing to take risks, which many economies, not least Americas, sorely need. Over the past three decades, Japan, Germany, and South Korea have aged almost twice as rapidly as the United States is aging right now, which means we have models to follow. The good news is their economies have not grown more slowly than those of other industrialized nations, and several of their labor dependent sectors, including cars, machine tools, and chemicals, haven't suffered. The reason is simple. They introduced new machinery, including industrial robots and other automation technologies, to take over the tasks younger employees would have performed. These countries also invested in training workers so that they could take on the new tasks that complement automation. German carmakers retrained their blue collar workers for more technical tasks such as repair, quality control, and digital machine operation while they rolled out robots. As a result, productivity has surged and wages have continued to increase. There's a scenario in which a shortage of labor could be a boon for the US Economy. Wages for lower educated workers stagnated or even declined between 1980 and the mid 2010s. Scarcity of labor can drive wages up, especially if combined with the right investments in both equipment and people. Alas, this isn't what is happening in the United States. Investment in robots has increased rapidly, but it hasn't been accompanied by adequate investments in people. The workforce remains unready for taking on new tasks, including technical and advanced precision work. It was the shortage of these types of skills that the Taiwan semiconductor manufacturing factory cited as a reason for delays in the opening of its first US Based chip factory. If the United States doesn't find ways to combine new machinery with better trained, more skilled, and more adaptable workers, the country risks more pain for manufacturing, the traditional provider of high wage, stable jobs. There are similar opportunities also likely to be wasted when it comes to artificial intelligence According to its most ardent fans, AI is the mother of all technological disruptions, the apogee of the digital age. Yet when you strip away the hype surrounding superintelligent algorithms, the AI challenge is remarkably similar to that of adapting to aging. AI is an information technology. It will not make your cake or mow your lawn. Nor will it take over the running of companies or scientific inquiry. Rather, it can automate a range of cognitive tasks that are typically performed in offices or in front of a computer. It can also provide better information to human decision makers, perhaps one day. Much better. None of this will happen rapidly. As of February 2024, only about 5% of businesses in the United States have reported using AI. And the technology itself is far from perfect. Google's AI struggled initially with questions about whether it's smart to eat rocks. Its spread in the economy will be slow, and its true impact won't be felt until the mid-2030s. The nature of that impact will depend on the readiness of corporations and workers. We need a broad national strategy so that AI doesn't only automate work and sideline workers, but creates new tasks and competencies for them. This isn't just because of the inequality that rapid AI based automation could create, or the fear of tech elites that the resulting joblessness will bring out the pitchforks. Evidence suggests that new technologies increase productivity much more consistently when they work with workers, enabling them to perform their jobs better and allowing them to expand into new, more sophisticated tasks. The secret sauce of Henry Ford's innovative car factories wasn't simply a more widespread use of better machinery, but also a whole range of technical tasks workers were trained for, such as repair and maintenance. Most of us today are involved in problem solving, whether an office worker making loan or hiring decisions, a scientist or journalist trying to get to the bottom of a question, or an electrician calling carpenter or craftworker dealing with malfunctions and other real world obstacles. Most of us can become more productive and expand our range if we get better information. Yet even more than with aging, it looks like we're going to mismanage this wave. The industry is locked into a race centered on artificial general intelligence, meaning the incuate dream of producing machines that are just like humans and can take over all tasks from us. It remains preoccupied with using this technology, either for generating digital ad revenue or for automation. The real promise of AI is unlikely to become reality by itself. It requires AI models to become more expert, better powered by higher quality data, more reliable, and more aligned with the existing knowledge and the information processing capabilities of workers. None of this appears to be at the top of Big Tech's agenda. One obvious policy to confront both the aging and the AI challenges is to encourage training of workers, for example, with tax credits or training subsidies, so that they can take on new tasks and jobs. Ms. Harris's economic plan puts much more emphasis on this than Mr. Trump's. Much more can be done. It isn't just that workers need to get ready. So do our technological capabilities. Here the federal government can play an important role, for example, via a new federal agency tasked with identifying and funding the types of AI that can increase worker productivity and help us deal with looming labor shortages. Globalization may appear like a different kettle of fish, but but there are major parallels. The era of rapid and largely unfettered globalization that followed the collapse of the Soviet Union is over. It benefited Western consumers and multinational corporations who got access to inexpensive labor overseas. Workers, not so much. What will replace globalization is less clear. It could be a fragmented system in which countries trade with allies and friends with broadly similar flows to what we are seeing today, say less of China and more of Vietnam. It could be one with high tariffs and much less trade. It could also be a combination of trade restrictions and industrial policies such as the Biden Administration's Inflation Reduction act and the CHIPS act, which are designed to encourage more investment in manufacturing, especially in advanced electronics, electric cars, and renewable technologies to stay in or to relocate to the United States. This change is also slow and has significant implications for workers. The promise of new manufacturing capabilities could lead to new job opportunities and possibly higher wages. On the other hand, new manufacturing competencies cannot be built overnight, and skills shortages can choke off industrial renewal. Alas, once again, the United States, and especially its workforce, isn't ready. The good news here is that we have time, and if we grab the opportunities presented by aging AI and the new globalization, they can all serve to improve one another. The skills that employers and schools need to tackle each of these huge shifts are similar. Moreover, the right kind of AI can greatly help us navigate the challenges posed by aging and the reshaping of globalization. The bad news is that these issues are not getting the attention they deserve, even though they are much more important for our future than debates about price.

Gouging, taxes on tips, or whether inflation.

Is 1 point higher or 1 point lower. Unless we focus on them and act decisively, they will not just be mismanaged but also may spell a more dire future of work.

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All right, back to Real Non AI NLW here. Like I said and caveated at the beginning, Acemoglu definitely has a different sense of how fast AI is coming down the horizon. This February 2024 stat of only about 5% of businesses in the U.S. for example, reporting using AI is, I think, wildly misleading and dramatically undersells one the organic bottoms up and often secret adoption happening and 2 the incredible pressure that enterprises face to actually figure out this technology. Still, that's not really the point here. In fact, if anything, all that really does is change the timescale on which Acemoglu thinks that we need to start having these conversations.

And to me, what's valuable about this.

Piece is that I do believe that almost no matter what you think, it is quite clear that that we need to be having a different and broader conversation about the nature of work, about the social contract and contributions to society.

About what we want out of the.

Economy than we're having today.

I have frequently said on this podcast.

And in speeches and in appearances, and basically anywhere that I can get a chance to, that the reason that I'm so bullish about AI in the long run is that I view it as a fundamentally opportunity expanding technology. I think it's going to allow people to create more, to do more, to build more. And I think that humans have shown throughout the course of history that we have a basically unending appetite to consume more, to participate in more.

So we are just going to live.

In a more world that is very hard from where we are now to imagine today. And I think that there's going to be an incredible new array of ways that people interact and operate within that world. However, I also believe that the transition to that world has the potential to be enormously painful and challenging. There are entire categories of, if not jobs, at least tasks, that comprise big chunks of jobs, that are going to change virtually overnight, certainly overnight if we're talking in the timescale of a career. I don't think any parent who has kids who will be going to college in the next five to 10 to 15 years really has any idea what they should tell their kids to study. And that, I think is just broadly representative of how much is likely to change. Now, the reason that I keep coming back to this idea of a broader conversation about the social contract is that I think that this is about more than just gainful employment. I think it's about a moment to ask what our relationship with work is in a world where AI can do a huge portion of jobs better than humans can. It's not going to just be about moving people to higher order tasks and different types of jobs. It's a moment to discuss what a reasonable contribution to society is, how much.

Of our meaning we should derive from.

Work, et cetera, et cetera, et cetera. Now, of course, these are highly philosophical topics, and what Darren Acemoglu is arguing for is just the political dimension of them, which is of course needed as well. I think for me, the TLDR is that the world that AI is enabling is, to some, scary to me and people who think like me, incredibly exciting. But to most who have spent any time with this technology, wildly different. Different does not mean bad, but it does usually mean volatility and challenge.

Figuring out how to spend time and.

Engage with that challenge meaningfully is probably worth our time. For now, though, that's going to do it for today's AI Daily brief. Until next time, Peace.