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Review of “Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity”

This new book on tech, AI, and economic prosperity by Daron Acemoglu and Simon Johnson is incredibly timely

This book by two MIT economists is very timely because the world is now dealing with the latest in the “Thousand Year Struggle,” in the form of artificial intelligence, the claims that many white-collar jobs will be automated, OpenAI’s call for regulation, and the possibility that AI will bring a further concentration of power among the big tech companies.

Much of the book sets the stage for this discussion by summarizing the history of technology. This review focuses on the economic and social impact of automation and information technology over the last 50 years. For instance,

“the distribution of income between capital and labor began to change significantly in the late 20th century. While throughout most of the century, about 67‒70% of national income went to workers, by 2019, labor’s share of national income had dropped to under 60 percent.”

Similar trends can be found outside of the U.S. in Europe and Japan as automation and offshoring proceeded.   

The book argues that the effects of automation technologies and the eclipse of rent sharing on inequality have been even more extensive than the consequences of offshoring, or what the book calls the “China shock.”

“Import competition from China impacted mostly low-value-added manufacturing sectors, such as textiles, apparel, and toys. Automation, on the other hand, has concentrated in higher-value-added and higher-wage manufacturing sectors, such as cars, electronics, metals, chemicals, and office work. It is the dwindling of this latter set of jobs that has played a more central role in the surge in inequality.”

This inequality can also be seen in the rise of America’s most dominant corporations: Google, Facebook, Apple, Amazon, and Microsoft. “They are jointly worth about one-fifth of US GDP” and do almost no manufacturing, although Amazon has warehouses. These companies also enjoy “extensive greater market power, which they are exercising both to thwart innovation from rivals and to enrich their top executives and shareholders.”

AI’s Impact on Productivity and Employment

The authors see little productivity coming from these huge corporations. “In 1987, Nobel Prize winner Robert Solow wrote: “You can see the computer age everywhere but in the productivity statistics,” pointing out the small gains from investments in digital technologies. Those more optimistic about computers told Solow that he had to be patient; productivity growth would soon be upon us. More than thirty-five years have passed, and we are still waiting. In fact, the US and most other Western economies have had some of the most unimpressive decades in terms of productivity growth since the beginning of the Industrial Revolution.” Focusing on total factor productivity (TFP), “US average growth since 1980 has been less than 0.7 percent, compared to TFP growth of approximately 2.2 percent between the 1940s and 1970s.”

One chapter is devoted to AI and its potential impact on productivity and employment. The book argues that:

“AI does not appear to be advancing so much that it will create mass joblessness,” even though this year’s hysteria about ChatGPT is included. Like the industrial robots that are discussed in a previous chapter, “current technology thus far can perform only a small set of tasks, and its impact on employment is limited. Nevertheless, it is heading in a direction that is biased against workers and is destroying some jobs. Its most major likely impact is to further lower wages for many people, not create a completely workless future. The problem is that although AI fails in most of what it promises, it still manages to reduce the demand for workers.”

All Data and No Privacy Makes for an Orwellian World

Another problem is that AI uses massive quantities of data. In the words of an AI scientist, Alberto Romero, who became disillusioned with the industry and left it in 2021: “If you work in AI you are most likely collecting data, cleaning data, labeling data, splitting data, training with data, evaluating with data. Data, data, data. All for a model to say: It’s a cat.” This focus on vast quantities of data is a fundamental consequence of our emphasis on autonomy, and a big source of anger as our privacy is diminished.

The book sees AI taking us further down the same road of stealing our privacy and worsening inequality by increasing the power of elites even while giving us much less measurable progress in terms of higher productivity and standard of living.

“Modern AI amplifies the tools in the hands of tech elites, enabling them to create more ways of automating work, sidelining humans, and supposedly doing all sorts of good deeds such as increasing productivity and solving major problems facing humanity (they claim).”

Near the end of the second to last chapter, the authors project the impact of AI:

Empowered by AI, these leaders feel even less need to consult the rest of the population. In fact, many of them think that most humans are not that wise and may not even understand what is good for them. The marriage of digital technologies and big business had created a growing number of billionaires by the mid-2000s. Such fortunes multiplied once AI tools started spreading in the 2010s.

But this was not because AI turned out to be anything as productive or amazing as its boosters have maintained. On the contrary, AI-based automation often fails to increase productivity by that much. Worse, it is no way to build shared prosperity. It nevertheless enthralls and enriches tycoons and top managers as it disempowers workers and opens up new ways of monetizing information about people.

That all of this gets ignored in a mad rush to use digital technologies to automate work and monitor humans is the reason why we have dubbed this new phase of the vision the AI illusion. This illusion is set to intensify in the next decade, as more powerful algorithms are developed, global online connectivity grows, and household appliances and other machines become permanently connected to the cloud, allowing more extensive data collection. Today we are moving closer to H. G. Wells’s Time Machine future dystopia.

Our society has already become two-tiered. On top there are the big tycoons, who firmly believe they have earned their wealth because of their amazing genius. At the bottom we have regular people whom tech leaders view as error-prone and ripe for replacement. As AI penetrates more and more aspects of modern economies, it looks increasingly likely that the two tiers will grow further apart.

The book is a well-grounded analysis of a highly controversial topic that has only become more inflammatory as calls for a “pause” and for more industry self-regulation increase. The book is also a great successor to Acemoglu’s previous book with James Robinson entitled Why Nations Fail. For those of you who have read it, you will see America rushing down the path that Acemoglu and Robinson warned us about. The authors of this book, Acemoglu and Johnson, are clearly not very optimistic about America’s future.

Jeffrey Funk

Fellow, Walter Bradley Center for Natural and Artificial Intelligence
Jeff Funk is a retired professor and a Fellow of Discovery Institute’s Walter Bradley Center for Natural and Artificial Intelligence. His book, Competing in the Age of Bubbles, is forthcoming from Harriman House.

Review of “Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity”