Power and Progress
* Book: Power and Progress. By Daron Acemoglu and Simon Johnson.
URL = https://www.hachettebookgroup.com/titles/daron-acemoglu/power-and-progress/9781541702530/?
Description
Aki Ito:
"Daron Acemoglu, an economist at MIT, is so prolific and respected that he's long been viewed as a leading candidate for the Nobel prize in economics. He used to believe in the conventional wisdom, that technology is always a force for economic good. But now, with his longtime collaborator Simon Johnson, Acemoglu has written a 546-page treatise that demolishes the Church of Technology, demonstrating how innovation often winds up being harmful to society. In their book "Power and Progress," Acemoglu and Johnson showcase a series of major inventions over the course of the past 1,000 years that, contrary to what we've been told, did nothing to improve, and sometimes even worsened, the lives of most people. And in the periods when big technological breakthroughs did lead to widespread good — the examples that today's AI optimists cite — it was only because ruling elites were forced to share the gains of innovation widely, rather than keeping the profits and power for themselves. It was the fight over technology, not just technology on its own, that wound up benefiting society.
"The broad-based prosperity of the past was not the result of any automatic, guaranteed gains of technological progress," Acemoglu and Johnson write. "We are beneficiaries of progress, mainly because our predecessors made the progress work for more people." Today, in this moment of peak AI, which path are we on?"
Discussion
Evidence for the Negative Historical Social Effects of Technological Progress
Aki Ito:
"Acemoglu and Restrepo, casting around for more empirical evidence, zeroed in on robots. What they found was stunning: Since 1990, the introduction of every additional robot reduced employment by approximately six humans, while measurably lowering wages. "That was an eye-opener," Acemoglu told me. "People thought it would not be possible to have such negative effects from robots."
Many economists, clinging to the technological orthodoxy, dismissed the effects of robots on human workers as a "transitory phenomenon." In the end, they insisted, technology would prove to be good for everyone. But Acemoglu found that viewpoint unsatisfying. Could you really call something that had been going on for three or four decades "transitory"? By his calculations, robots had thrown more than half a million Americans out of work. Perhaps, in the long run, the benefits of technology would eventually reach most people. But as the economist John Maynard Keynes once quipped, in the long run, we're all dead.
o Acemoglu set out to study the long run. First, he and Johnson scoured the course of Western history to see whether there were other times when technology failed to deliver on its promise. Was the recent era of automation, as many economists assumed, an anomaly?
It wasn't, Acemoglu and Johnson found. Take, for instance, medieval times, a period commonly dismissed as a technological wasteland. But the Middle Ages actually saw a series of innovations that included heavy wheeled plows, mechanical clocks, spinning wheels, smarter crop-rotation techniques, the widespread adoption of wheelbarrows, and a greater use of horses. These advancements made farming much more productive. But the reason we remember the period as the Dark Ages is precisely because the gains never reached the peasants who were doing the actual work. Despite all the technological advances, they toiled for longer hours, grew increasingly malnourished, and most likely lived shorter lives. The surpluses created by the new technology went almost exclusively to the elites who sat at the top of society: the clergy, who used their newfound wealth to build soaring cathedrals and consolidate their power.
Or consider the Industrial Revolution, which techno-optimists gleefully point to as Exhibit A of the invariable benefit of innovation. The first, long stretch of the Industrial Revolution was actually disastrous for workers. Technology that mechanized spinning and weaving destroyed the livelihoods of skilled artisans, handing textile jobs to unskilled women and children who commanded lower wages and virtually no bargaining power. People crowding into the cities for factory jobs lived next to cesspools of human waste, breathed coal-polluted air, and were defenseless against epidemics like cholera and tuberculosis that wiped out their families. They were also forced to work longer hours while real incomes stagnated. "I have traversed the seat of war in the peninsula," Lord Byron lamented to the House of Lords in 1812. "I have been in some of the most oppressed provinces of Turkey; but never, under the most despotic of infidel governments, did I behold such squalid wretchedness as I have seen since my return, in the very heart of a Christian country."
If the average person didn't benefit, where did all the extra wealth generated by the new machines go? Once again, it was hoarded by the elites: the industrialists. "Normally, technology gets co-opted and controlled by a pretty small number of people who use it primarily to their own benefits," Johnson told me. "That is the big lesson from human history."
Acemoglu and Johnson recognized that technology hasn't always been bad: At times, they found, it's been nothing short of miraculous. In England, during the second phase of the Industrial Revolution, real wages soared by 123%. The average working day declined to nine hours, child labor was curbed, and life expectancy rose. In the United States, during the postwar boom from 1949 to 1973, real wages grew by almost 3% a year, creating a vibrant and stable middle class. "There has never been, as far as anyone knows, another epoch of such rapid and shared prosperity," Acemoglu and Johnson write, going all the way back to the Ancient Greeks and Romans. It's episodes like these that made economists believe so fervently in the power of technology.
So what separates the good technological times from the bad? That's the central question that Acemoglu and Johnson tackle in "Power and Progress." Two factors, they say, determine the outcome of a new technology. The first is the nature of the technology itself — whether it creates enough new tasks for workers to offset the tasks it takes away. The first phase of the Industrial Revolution, they argue, was dominated by textile machines that replaced skilled spinners and weavers without creating enough new work for them to pursue, condemning them to unskilled gigs with lower wages and worse conditions. In the second phase of the Industrial Revolution, by contrast, steam-powered locomotives displaced stagecoach drivers — but they also created a host of new jobs for engineers, construction workers, ticket sellers, porters, and the managers who supervised them all. These were often highly skilled and highly paid jobs. And by lowering the cost of transportation, the steam engine also helped expand sectors like the metal-smelting industry and retail trade, creating jobs in those areas as well.
The second factor that determines the outcome of new technologies is the prevailing balance of power between workers and their employers. Without enough bargaining power, Acemoglu and Johnson argue, workers are unable to force their bosses to share the wealth that new technologies generate. And what determines the degree of bargaining power is closely related to democracy. Electoral reforms — kickstarted by the working-class Chartist movement in 1830s Britain — were central to the Industrial Revolution transforming from bad to good. As more men won the right to vote, Parliament became more responsive to the needs of the broader public, passing laws to improve sanitation, crack down on child labor, and legalize trade unions. The growth of organized labor, in turn, laid the groundwork for workers to extract higher wages and better working conditions from their employers in the wake of technological innovations, along with guarantees of retraining when new machines took over their old jobs.
In normal times, such insights might feel purely academic — just another debate over how to interpret the past. But there's one point that both Acemoglu and the tech elite he criticizes agree on: We're in the midst of another technological revolution today with AI. "What's special about AI is its speed," Acemoglu told me. "It's much faster than past technologies. It's pervasive. It's going to be applied pretty much in every sector. And it's very flexible. All of this means that what we're doing right now with AI may not be the right thing — and if it's not the right thing, if it's a damaging direction, it can spread very fast and become dominant. So I think those are big stakes.""
Interview
Daron Acemoglu:
"The main thesis of Power and Progress is that technology does, to some extent, what we want it to do. It does not have a preordained destiny that will take us in one direction or another. We have a lot of agency, a lot of choice in shaping the future of technology, and different futures correspond to different winners and losers, different benefits, different costs, different productivities.
We tried to make that point by going into history, showing how critical periods during our recent history, like the last 1,000 years, have led to sometimes big technological breakthroughs but with huge losers, and sometimes those forces have been reversed, and gains from technological betterment have been shared more equitably. That message, I think, is more relevant today than ever. AI is a particularly versatile technology. It provides so many different futures for us.
The narrative that there is a determined natural future of AI, and we are all going there whether we want it or not — and, ultimately, we’re all going to become incredibly more prosperous out of that — is just simplistic. Fighting against that narrative, I think, is very important today because that narrative lulls us into a sense of helplessness and sense of complacence that could be quite costly. On the other hand, of course, in 2021, 2022, when we were writing, it was impossible to foresee how rapid some of the advances in generative AI would be. But those advances haven’t really changed the basic trade-offs and the basic messages that we wanted to convey in the book.
I talked at the high level about different directions of AI. What are they? I think, simplifying it, you have a couple of poles that are pulling in different directions. I would single out — in the production process — automation, which is the dream of most AI models today, especially under the banner of artificial general intelligence (AGI), which aims for large language models or other generative AI tools to reach levels of capabilities comparable to the best workers across a very wide range of domains. The reason why that is viewed as attractive is that just like previous rounds of software that improved cognition in different domains, that can then be used for automating tasks. So AGI is very tightly interwoven with the automation agenda. Automation is great. It gets rid of some routine tasks, some boring tasks.
When it’s applied in the physical domain, such as with cranes or robots, it could remove the most dangerous tasks from the human work schedule, but automation also doesn’t benefit workers by itself. It takes away tasks from workers. It is beneficial to capital and capital owners and not so much for workers in general.
So at the other pole, we have things that are complementary to humans, meaning that technology enables humans to do more things or better things or completely new things. These new things [are] what I refer to as new tasks. So if you look at people around you, many of the occupations you’ll see involve things that could not even be imagined 50 or 60 years ago. As a journalist, you’re going to be making videocasts and podcasts and [using] technologies for research that require completely different skills than somebody 60 years ago going to the library and sifting through books. Those are some aspects of new tasks. So are many of the physical occupations in manufacturing that involve much more technical work. Those have generally been very good for productivity and for worker wages and employment.
That’s one dimension in which the future of technology could have very different effects depending on whether we go [in] the automation or the new task direction. I would also like to add, whether we use technology for information centralization or decentralization is also important in that many of the early hopes about computers were centered on decentralization. People could [do things] in their garages that IBM as a centralized organization couldn’t do. Personal computers enabled that to some extent, not anywhere comparable to the hopes of pioneers of computing in the ’60s and the ’70s.
But today, we are going in the opposite direction. Large language models are information centralization tools. They collect all of the information. They aim to collect all of the information of humanity ultimately, and then centralize that and process that in a centralized manner that then gives you answers. So there’s less for the decentralized human mind and human participation to do.
Centralization and automation are two different poles, but they are complementary."
(https://sloanreview.mit.edu/audio/ai-is-not-improving-productivity-nobel-laureate-daron-acemoglu/)