Tag: Productivity

Is it 1987 for AI?

Image generated by ChatGPT 5 of a 1981 IBM personal computer.

The modern era of information technology began in the 1980s with the spread of personal computers. A key development was the introduction of the IBM personal computer in 1981. The Apple II, designed by Steve Jobs and Steve Wozniak and introduced in 1977, was the first widely used personal computer, but the IBM personal computer had several advantages over the Apple II. For decades, IBM had been the dominant firm in information technology worldwide. The IBM System/360, introduced in 1964, was by far the most successful mainframe computer in the world. Many large U.S. firms depended on IBM to meet their needs for processing payroll, general accounting services, managing inventories, and billing.

Because these firms were often reliant on IBM for installing, maintaining, and servicing their computers, they were reluctant to shift to performing key tasks with personal computers like the Apple II. This reluctance was reinforced by the fact that few managers were familiar with Apple or other early personal computer firms like Commodore or Tandy, which sold the TRS-80 through Radio Shack stores. In addition, many firms lacked the technical staffs to install, maintain, and repair personal computers. Initially, it was easier for firms to rely on IBM to perform these tasks, just as they had long been performing the same tasks for firms’ mainframe computers.

By 1983, the IBM PC had overtaken the Apple II as the best-selling personal computer in the United States. In addition, IBM had decided to rely on other firms to supply its computer chips (Intel) and operating system (Microsoft) rather than develop its own proprietary computer chips and operating system. This so-called open architecture made it possible for other firms, such as Dell and Gateway, to produce personal computers that were similar to IBM’s. The result was to give an incentive for firms to produce software that would run on both the IBM PC and the “clones” produced by other firms, rather than produce software for Apple personal computers. Key software such as the spreadsheet program Lotus 1-2-3 and word processing programs, such as WordPerfect, cemented the dominance of the IBM PC and the IBM clones over Apple, which was largely shut out of the market for business computers.

As personal computers began to be widely used in business, there was a general expectation among economists and policymakers that business productivity would increase. Productivity, measured as output per hour of work, had grown at a fairly rapid average annual rate of 2.8 percent between 1948 and 1972. As we discuss in Macroeconomics, Chapter 10 (Economics, Chapter 20 and Essentials of Economics, Chapter 14) rising productivity is the key to an economy achieving a rising standard of living. Unless output per hour worked increases over time, consumption per person will stagnate. An annual growth rate of 2.8 percent will lead to noticeable increases in the standard of living.

Economists and policymakers were concerned when productivity growth slowed beginning in 1973. From 1973 to 198o, productivity grew at an annual rate of only 1.3 percent—less than half the growth rate from 1948 to 1972. Despite the widespread adoption of personal computers by businesses, during the 1980s, the growth rate of productivity increased only to 1.5 percent. In 1987, Nobel laureate Robert Solow of MIT famously remarked: “You can see the computer age everywhere but in the productivity statistics.” Economists labeled Solow’s observation the “productivity paradox.” With hindsight, it’s now clear that it takes time for businesses to adapt to a new technology, such as personal computers. In addition, the development of the internet, increases in the computing power of personal computers, and the introduction of innovative software were necessary before a significant increase in productivity growth rates occurred in the mid-1990s.

Result when ChatGPT 5 is asked to create an image illustrating ChatGPT

The release of ChatGPT in November 2022 is likely to be seen in the future as at least as important an event in the evolution of information technology as the introduction of the IBM PC in August 1981. Just as with personal computers, many people have been predicting that generative AI programs will have a substantial effect on the labor market and on productivity.

In this recent blog post, we discussed the conflicting evidence as to whether generative AI has been eliminating jobs in some occupations, such as software coding. Has AI had an effect on productivity growth? The following figure shows the rate of productivity growth in each quarter since the fourth quarter of 2022. The figure shows an acceleration in productivity growth beginning in the fourth quarter of 2023. From the fourth quarter of 2023 through the fourth quarter of 2024, productivity grew at an annual rate of 3.1 percent—higher than during the period from 1948 to 1972. Some commentators attributed this surge in productivity to the effects of AI.

However, the increase in productivity growth wasn’t sustained, with the growth rate in the first half of 2025 being only 1.3 percent. That slowdown makes it more likely that the surge in productivity growth was attributable to the recovery from the 2020 Covid recession or was simply an example of the wide fluctuations that can occur in productivity growth. The following figure, showing the entire period since 1948, illustrates how volatile quarterly rates of productivity growth are.

How large an effect will AI ultimately have on the labor market? If many current jobs are replaced by AI is it likely that the unemployment rate will soar? That’s a prediction that has often been made in the media. For instance, Dario Amodei, the CEO of generative AI firm Anthropic, predicted during an interview on CNN that AI will wipe out half of all entry level jobs in the U.S. and cause the unemployment rate to rise to between 10% and 20%.  

Although Amodei is likely correct that AI will wipe out many existing jobs, it’s unlikely that the result will be a large increase in the unemployment rate. As we discuss in Macroeconomics, Chapter 9 (Economics, Chapter 19 and Essentials of Economics, Chapter 13) the U.S. economy creates and destroys millions of jobs every year. Consider, for instance, the following table from the most recent “Job Openings and Labor Turnover” (JOLTS) report from the Bureau of Labor Statistics (BLS). In June 2025, 5.2 million people were hired and 5.1 million left (were “separated” from) their jobs as a result of quitting, being laid off, or being fired.

Most economists believe that one of the strengths of the U.S. economy is the flexibility of the U.S. labor market. With a few exceptions, “employment at will” holds in every state, which means that a business can lay off or fire a worker without having to provide a cause. Unionization rates are also lower in the United States than in many other countries. U.S. workers have less job security than in many other countries, but—crucially—U.S. firms are more willing to hire workers because they can more easily lay them off or fire them if they need to. (We discuss the greater flexibility of U.S. labor markets in Macroeconomics, Chapter 11 (Economics, Chapter 21).)

The flexibility of the U.S. labor market means that it has shrugged off many waves of technological change. AI will have a substantial effect on the economy and on the mix of jobs available. But will the effect be greater than that of electrification in the late nineteenth century or the effect of the automobile in the early twentieth century or the effect of the internet and personal computing in the 1980s and 1990s? The introduction of automobiles wiped out jobs in the horse-drawn vehicle industry, just as the internet has wiped out jobs in brick-and-mortar retailing. People unemployed by technology find other jobs; sometimes the jobs are better than the ones they had and sometimes the jobs are worse. But economic historians have shown that technological change has never caused a spike in the U.S. unemployment rate. It seems likely—but not certain!—that the same will be true of the effects of the AI revolution. 

Which jobs will AI destroy and which new jobs will it create? Except in a rough sense, the truth is that it is very difficult to tell. Attempts to forecast technological change have a dismal history. To take one of many examples, in 1998, Paul Krugman, later to win the Nobel Prize, cast doubt on the importance of the internet: “By 2005 or so, it will become clear that the Internet’s impact on the economy has been no greater than the fax machine’s.” Krugman, Amodei and other prognosticators of the effects of technological change simply lack the knowledge to make an informed prediction because the required knowledge is spread across millions of people. 

That knowledge only becomes available over time. The actions of consumers and firms interacting in markets mobilize information that is initially known only partially to any one person. In 1945, Friedrich Hayek made this argument in “The Use of Knowledge in Society,” which is one of the most influential economics articles ever written. One of Hayek’s examples is an unexpected decrease in the supply of tin. How will this development affect the economy? We find out only by observing how people adapt to a rising price of tin: “The marvel is that … without an order being issued, without more than perhaps a handful of people knowing the cause, tens of thousands of people whose identity could not be ascertained by months of investigation are made [by the increase in the price of tin] to use the material or its products more sparingly.” People adjust to changing conditions in ways that we lack sufficient information to reliably forecast. (We discuss Hayek’s view of how the market system mobilizes the knowledge of workers, consumers, and firms in Microeconomics, Chapter 2.)

It’s up to millions of engineers, workers, and managers across the economy, often through trial and error, to discover how AI can best reduce the cost of producing goods and services or improve their quality. Competition among firms drives them to make the best use of AI. In the end, AI may result in more people or fewer people being employed in any particular occupation.  At this point, there is no way to know.

 

Glenn on Economic Populism

Ninteenth century populist William Jennings Bryan delivering a campaign speech. (Photo from the AP via politico.com)

The following op-ed originally appeared in the Wall Street Journal.

The Economic Populists Have a Point

Many issues divide voters heading into the November election, but the economy may be the most crucial. Sound economic policy can foster prosperity and high living standards and affect income and opportunities. Economic resources can also enable society to fund defense or address social and environmental concerns.

Conservative economic policy traditionally has emphasized the openness of markets and growth. By contrast, the populist conservative ideas under discussion at the Republican National Convention focus on people and places hard hit by the disruption that accompanies openness and growth. While many commentators emphasize the differences between the two approaches, a modern conservative economic agenda should build on elements of both.

To begin, a conservative economic agenda should include policies that advance economic growth and living standards. That means supporting research and development, maintaining pro-investment business tax provisions in the Tax Cuts and Jobs Act of 2017, and making regulations that benefit everyone. Such an economy lets businesses and individuals get the most out of the opportunities they seize.

Populist conservatives argue that this traditional approach to policy misses an important objective: a disruptive, rough-and-tumble economy, guided by technological advances and globalization, one that brings everyone along. Populist conservatives want more emphasis on protecting jobs and communities.

There’s more to the populist conservatives’ skepticism than traditional conservatives acknowledge. But backward-looking protectionist measures such as inflationary tariffs or industrial policy aren’t the answer.

However, there is a conservative economic agenda that can unite these groups. The shortcomings of Bidenomics give conservatives an opening to push beyond both market-only neoliberalism and the statist tendencies of industrial policy and protectionism, with their attendant economic inefficiencies. To do so, conservative economic policy needs three ingredients.

The first is agreeing with populist conservatives that markets don’t always work perfectly and that a hands-off approach isn’t always the solution. The state can play a useful role in the market economy. Supply-chain restrictions and export controls can be tools to deny national-security-sensitive technologies to adversaries such as China. But an economic agenda requires more than a sound bite to avoid overreach—such as using “national security” as a pretext for slapping steel tariffs on Canada.

The second essential is competition—the linchpin of economic possibilities for classical economic thinkers from Adam Smith onward. While competition at home and abroad expands the economic pie, it says little about the relative sizes of the slices, a point noted by populist conservatives. A modern conservative economic approach would not only promote competition but also prepare more individuals to compete in a changing economy. One avenue could be supporting community colleges that understand local job needs rather than establishing more government training programs.

Third and most important, a conservative economic platform should recall why conservatives have stressed the benefits of markets. The goal, as my Columbia colleague and Nobel laureate Edmund Phelps puts it, is “mass flourishing.” That is why we want markets to work—to advance innovation and productivity and allow communities to make that flourishing possible.

As far as government’s role, a contemporary economic agenda should recognize a limited measure of successful industrial policy. Two roads should be on offer. The first is to provide more general support for basic and applied research, while letting market forces determine winners and losers. The second is to assign specific goals to particular interventions. The Apollo program’s goal was to put a man on the moon in a decade. The Trump administration’s Operation Warp Speed sought vaccines against Covid. 

Populist conservatives are right that there is a role in a conservative economic agenda for helping areas hard hit by disruption. But that role isn’t a mercantilist blunderbuss of protectionism and industrial policy to turn back the economic clock. Rather, place-based aid could support business services for firms trying to create local jobs.

The economic ideas under discussion at the Republican National Convention have populist features that haven’t figured in earlier conservative economic agendas. Populists have some reasonable skepticism about excessive deference to markets. But avoiding excessive meddling from tempting protectionism and the mushy mercantilism of Bidenomics is important, too. Under a conservative economic agenda, growth can flourish.

Glenn’s Op-Ed on the Need for Pro-Growth Policies

(Photo from the New York Times.)

This op-ed orginally appeared in the Wall Street Journal.

Put Growth Back on the Political Agenda

In a campaign season dominated by the past, a central economic topic is missing: growth. Rapid productivity growth raises living standards and incomes. Resources from those higher incomes can boost support for public goods such as national defense and education, or can reconfigure supply chains or shore up social insurance programs. A society without growth requires someone to be worse off for you to be better off. Growth breaks that zero-sum link, making it a political big deal.

So why is the emphasis on growth fading? More than economics is at play. While progress from technological advances and trade generally is popular, the disruption that inevitably accompanies growth and hits individuals, firms and communities has many politicians wary. Such concerns can lead to excessive meddling via industrial policy.

As we approach the next election, the stakes for growth are high. Regaining the faster productivity that prevailed before the global financial crisis requires action. The nonpartisan Congressional Budget Office estimates  potential gross domestic product growth of 1.8% over the coming decade, and somewhat lower after that. Those figures are roughly 1 percentage point lower than the growth rate over the three decades before the pandemic. Many economists believe productivity gains from generative artificial intelligence can raise growth in coming decades. But achieving those gains requires an openness to change that is rare in a political climate stuck in past grievances about disruption—the perennial partner of growth.

Traditionally, economic policy toward growth emphasized support for innovation through basic research. Growth also was fostered by reducing tax burdens on investment, streamlining regulation (which has proliferated during the Biden administration) and expanding markets. These important actions have flagged in recent years. But such attention, while valuable, masks inattention to adverse effects on some individuals and communities, raising concerns about whether open markets advance broad prosperity.

This opened a lane for backward-looking protectionism and industrial policy from Democrats and Republicans alike. Absent strong national-defense arguments (which wouldn’t include tariffs on Canadian steel or objections to Japanese ownership of a U.S. steel company), protectionism limits growth. According to polls by the Chicago Council on Global Affairs, roughly three-fourths of Americans say international trade is good for the economy. Finally, protectionism belies ways in which gains from openness may be preserved, such as by simultaneously offering support for training and work for communities of individuals buffeted by trade and technological change.

On industrial policy, it is true that markets can’t solve every allocation problem. But such concerns underpin arguments for greater federal support of research for new technologies in defense, climate-change mitigation, and private activity, not micromanaged subsidies to firms and industries. If a specific defense activity merits assistance, it could be subsidized. These alternatives mitigate the problems in conventional industrial policy of “winner picking” and, just as important, the failure to abandon losers. It is policymakers’ hyperattention to those buffeted by change that hampers policy effectiveness and, worse, invites rent-seeking behavior and costly regulatory micromanagement.

Examples abound. Appending child-care requirements to the Chips Act and the inaptly named Inflation Reduction Act has little to do with those laws’ industrial policy purpose. The Biden administration’s opposition to Nippon Steel’s acquisition of U.S. Steel raises questions amid the current wave of industrial policy. How is a strong American ally’s efficient operation of an American steel company with U.S. workers an industrial-policy problem? Flip-flops on banning TikTok fuel uncertainty about business operations in the name of industrial policy.

The wrongly focused hyperattention is supposedly grounded in putting American workers first. But it raises three problems. First, the interventions raise the cost of investments, and the jobs they are to create or protect, by using mandates and generating policy uncertainty. Second, they contradict the economic freedom in market economies of voluntary transactions. Absent a strong national-security foundation, why is public policy directing investment in or ownership of assets? Such policies threaten the nation’s long-term prosperity by discouraging investment and invite rent-seeking in a way that voluntary market transactions don’t. Both problems hamstring growth. 

Third, and perhaps most important, such micromanagement misses the economic and political mark of actually helping individuals and communities disrupted by growth-enhancing openness. A more serious agenda would focus on training suited to current markets (through, for example, more assistance to community colleges), on work (through expanding the Earned Income Tax Credit), and on aid to communities hit by prolonged employment loss (through services that enhance business formation and job creation). The federal government could also establish research centers around the country to disseminate ideas for businesses. 

Growth matters—for individual livelihoods, business opportunities and public finances. Pro-growth policies that account for disruption’s effects while encouraging innovation, saving, capital formation, skill development and limited regulation must return to the economic agenda. A shift to prospective, visionary thinking would reorient the bipartisan, backward-looking protectionism and industrial policy that weaken growth and fail to address disruption.

11/06/20 Podcast – Authors Glenn Hubbard & Tony O’Brien discuss the economic outlook given where the Presidential election stands.

Authors Glenn Hubbard and Tony O’Brien look at the economic outlook given the current status of the presidential election. Will a divided government lead to economic prosperity or result in more gridlock? They discuss how much the President actually controls economic policy by setting the tone but that other instruments of our government likely have more effect in creating long-term growth in the Economy.

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