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 I occasionally pause for a moment to remember that just a few years ago, before we were concerned that AI would take all the jobs, we were worried that new robotics technologies would take all the jobs. And before that, we were worried that automation would take all the jobs. Can we learn something from previous industrial revolutions about how the current one?Arthur H. Goldsmith delivered the Presidential Address to the Southern Economic Association in 2022 on “The 4th Industrial Revolution and the Future of Work: Reasons to Worry and Policies to Consider.” The written version (co-authored with James F. Casey) is now posted online prior to publication in the Southern Economic Journal.What were the first three industrial revolutions? As Goldsmith tells it:

The First IR emerged in England around 1765 with the advent of the steam engine to mechanize production, especially in the agriculture, mining, and transportation sectors. … The Second IR arrived in 1865, roughly a 100 years after the first. New sources of power—electricity and the internal combustion engine—were the signature technological advancements of the Second IR. … The Third IR—the Digital Revolution—begins around 1970, once again about a century after the preceding IR. Digitization entails representing information in bits, and the 3rd IR is about how a new collection of machines, and advances in coding (i.e., HTML) are used to—store, transfer, and analyze data (Goldfarb & Tucker, 2019). Introduction of the personal computer, super computers, and the internet of things enabled automation of industrial processes, space exploration, and dramatic advances in telecommunications, and science through research and development, such as the Human Genome Project.

So what’s the Fourth Industrial Revolution? Goldsmith argues that the technological changes of the last decade or two are not just a continuation of the Digital Revolution, but qualify as a separate Industrial Revolution:

Building on the era of digitization a dazzling array of new technologies have emerged in recent years including—3-D printing, nanotechnology, artificial intelligence, machine learning, quantum computing, big data, and cloud storage. Simultaneously, there have been vast improvements in existing technologies such as industrial robots, vision systems, sensors, and algorithms. The 4th IR is the result of integrating these technologies in creative and productive ways with robotics and artificial intelligence at the center of the transformation. Perhaps the most visible form of this evolution is Generative AI, which combines machine learning and artificial intelligence—guided by the architecture of the human brain—to learn about countless relations and patterns through exposure to vast amounts of data. This technology is then capable of producing data including text, images, audio, and code. …

The velocity, scope, and systems (i.e., production, management, and governance) impact of the 4th IR is striking. Robot density, the number of industrial bots per 10,000 workers, a standard barometer of manufacturing automation doubled globally between 2017 and 2022 (Heer, 2021, 2024)—an extraordinary pace—while in the U.S. robot density more than tripled between 1995 and 2017 (Bharadwaj & Dvorkin, 2019) and rose another 12% between 2020 and 2022. Likewise, the velocity of artificial intelligence activity in recent years is impressive. Corporate artificial intelligence investment spending in the U.S. rose by 423%, from 13 to 68 billion, between 2015 and 2020 (Statista Research Team, 2022), and global growth in artificial intelligence investment advanced at an even greater rate (Thormundsson, 2023) from 13 billion in 2015 to 92 billion in 2022.

The reader will note that by Goldsmith’s accounting, the US and global economy is really just at the start of this fourth Industrial Revolution. Thus, discussions about what effects it will have are necessarily speculative. As he writes: “An overarching question is will automation reduce the number of jobs or will mechanization generate so many new positions employment, on net, rises?”I confess that I am skeptical of phrasing the issue in terms of total jobs. An economist pointed out to me long ago that the single biggest determinant of the number of jobs in any economy is the population of the country. Thus, it seems to me as if the key issues are not about raw number of jobs, but about whether this industrial revolution will lead either to historically high levels of persistent unemployment, or to a pattern with usual levels of unemployment, but a higher share of workers in lower-wage jobs. Goldsmith argues the point this way:

This is the fundamental conceptual difference between the 4th IR and prior industrial revolutions during which advances in technology were considered skill-neutral—they improved the productivity and workplace outcomes for workers with different levels of formal education. The impact of this difference, skill-biased versus skill neutral, is profound, since it will undermine the job prospects and earnings for those with modest formal educational attainment—persons in the middle class—while advancing the economic situation for individuals who possess high levels of formal education.

At least to me, it isn’t obvious that the 4th Industrial Revolution is different in this way. I’ve been reading for decades that the 3rd Industrial Revolution involved “skill-based” technical change, and in this way helped to generate growing inequality of incomes since about 1980. In addition, the very limited evidence now available on effects of artificial intelligence tools in the workplace suggests that they can be especially valuable to lower-skill workers, rather than higher-skill workers. The underlying reason is that AI tools in effect can make pre-existing expertise more available to everyone, which is a bigger boost for those with less experience or lower skill.But while it isn’t (yet) clear to me that AI will lead to bigger technological displacement of workers than previous industrial revolutions, it nonetheless remains true that–in a healthy economy which is ever-shifting and ever-evolving–some workers will find that the skills and experience they developed in an existing job are no longer valued as highly in the market. In response to this ongoing issue, I’ve argued in the past for “active labor market policies” (for example, here and here). The US currently emphasizes “passive” labor market policies like paying unemployment insurance or providing safety net support to low-income households, while “active” labor market policies would expand the government role in job search and training.In particular, Goldsmith emphasized a potential role for the federal government as a coordinator and accreditation mechanism for “certificate programs.” As Goldsmith points out, private firms like Google have taken some prominent steps in this direction already:

Google rolled out the Google Career Certificate Program—a skill development initiative—in 2020 (Google, 2021; Hess, 2020). The Program offers Certificates in: IT Support, Data Analytics, Project Management, UX Design, and Android Development. The curriculum for each certificate was developed by Google and is taught by Google employees, solely online, using the learning platform Coursera. These certificate programs are self-paced, designed to be completed in 3–6 months, and admission does not require a college degree. It costs $49 a month to use the Coursera platform, and Google has funded 100,000 need-based scholarships for eligible applicants. In addition, Google awarded $10 million in grants to three nonprofits that partner with Google to provide workforce development to targeted groups including women, veterans, and underrepresented groups. The Google Career Certificates Employer Consortium (Google, 2024) includes over 150 U.S. companies including Deloitte, Target, and Verizon who consider Google Career Certificate graduates for entry-level jobs, which typically require a four-year college degree. Moreover, certificate holders have access to an exclusive job platform where they are fast-tracked when applying for jobs with Consortium employers. This initiative could be scaled up by the inclusion of additional firms and the government independently developing, or codeveloping, additional certificate programs, and leading the delivery.

To me, a main challenge for certificate programs is one of focus: each one needs to be laser-focused on specific skills, and not get loaded up with a bunch of other topics and skills that might be nice, but should be separated off into a different certificate. This kind of focus helps to keep down costs of the program and the time needed to qualify for the certificate, and thus will encourage workers to see it as a viable option.More By This Author:A Federal Guarantee Of Paid Vacation? Larry Summers On The Economics Of AIA Prescription For Fixing The US Healthcare System