Highlights: #161 – Michael Webb on whether AI will soon cause job loss, lower incomes, and higher inequality — or the opposite
Oct 19, 2023
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Michael Webb discusses the impact of AI on job loss and economy, including examples of increased employment. The podcast also explores the time it took for previous game-changing technologies to have economy-wide effects. The slow adoption of technology and the challenges of regulating AI are also discussed.
Low-skilled and low-paid jobs are most exposed to job loss from robots, while upper-middle skilled jobs are most vulnerable to AI.
Automation can lead to job displacement, but it also creates new employment opportunities and increases demand for related services.
Deep dives
Impact of Automation on Jobs and Skills
The podcast explores the impact of automation on jobs and skills. The speaker discusses how different technologies, such as robots, software, and artificial intelligence (AI), affect various skill levels of jobs. For robots, low-skilled and low-paid jobs are most exposed, while high-skilled jobs are less vulnerable. Software, however, impacts middle-skilled jobs the most, while low and high-skilled jobs are relatively less affected. On the other hand, AI shows a different pattern, with upper-middle skilled jobs being the most exposed. Additionally, the speaker mentions that the most regulated jobs, like doctors and lawyers, have the power to resist the potential disruption caused by automation. Overall, the discussion highlights the varying impact of automation on different skill levels and emphasizes the importance of considering both job exposure and regulatory factors.
How Automation Can Create Jobs
The podcast episode delves into the idea that automation does not necessarily lead to job loss but can actually create new employment opportunities. The speaker offers the example of automated teller machines (ATMs) and how their implementation reduced the need for humans in cash handling tasks. However, this automation also led to a decrease in costs for banks, enabling them to open more branches and expand their services. This expansion countered the initial job reduction caused by ATMs, ultimately resulting in a net increase in employment. The speaker highlights the concept of demand elasticity and complementarity, explaining how automation can lower costs and increase demand for related services, thus leading to the creation of new jobs that focus on higher-value activities.
Impact of Automation at the Individual Level
The podcast explores the impact of automation on individuals at the personal level. While acknowledging that automation can lead to job displacement for some individuals, the speaker emphasizes that it does not eliminate employment opportunities entirely. They discuss the concept of natural wastage, where people transition out of jobs through retirement, better job offers, or other factors. The speaker also addresses the influence of geography on job displacement. Young individuals in cities often have more options and opportunities to adapt to changing job markets, while older individuals in towns where a single employer dominates can face challenges in finding alternative employment. This highlights the importance of considering the individual experiences and circumstances when evaluating the effects of automation.
Comparing the Adoption Rate of AI with Other Technologies
The podcast examines the adoption rate of artificial intelligence (AI) compared to previous game-changing technologies, such as electricity and information technology (IT). It reveals an interesting parallel, as both AI and IT had a similar adoption rate. It took around 30 years to reach 50% adoption for both technologies. The discussion emphasizes the time it takes for technologies to diffuse and become widespread. The speaker also raises the point that while the technology improves rapidly, the adoption and integration into various industries and processes can be a slow process due to factors like cost, retooling, and resistance to change. By looking at historical examples, the speaker suggests that despite the speed of technological advancement, societal and economic constraints continue to shape the pace of adoption.
These aren't necessarily the most important, or even most entertaining parts of the interview — and if you enjoy this, we strongly recommend checking out the full episode:
