Beyond that, let’s add to the Marcus Chen portfolio. Let’s talk about Stacey Smith, a hypothetical health insurance claims adjuster. She and millions of people like her are employed in the U.S. in insurance and banking because of regulatory reasons that those jobs could not be off-shored. But now a lot of those approvals, whether it’s mortgage underwriting or claims adjusting, are easily done by A.I. agents — more consistently, more easily able to detect fraud, much more cheaply. What’s going to happen to the Stacey Smiths who are making a decent wage in places like Kentucky and Mississippi?
What about Bob Johnson? Let’s talk about him. He is a long-distance truck driver. He is one of three and a half million truck drivers in the U.S. who again make a decent wage. They live in the South, they live in Texas, Louisiana, Mississippi. They are the breadwinners for their family. They’re the pillars of their community. What happens when the Waymo technology diffuses and we get past regulatory barriers to the Bob Johnsons?
So maybe Marcus has a great outcome. What about Stacey? What about Bob?
BALL: I think if we want to get into specific industries or roles, the obvious ones are consulting, marketing, customer service, entry-level legal work, administrative work. All that is definitely real.
And then there’s this fuzzy layer of things in the physical world. I’m kind of doubtful that a humanoid robot’s going to be making you a cocktail at a bar, even if it could, right? People don’t want that. And that’s a very important thing for thinking about the future of work. What are people’s preferences going to be? Similarly, a lot of knowledge work, in the end, especially as you move up the ranks, comes down to persuading people of things. I find myself skeptical that the process of internal politicking within a firm or another organization is just going to be automated away by A.I.
MOLLICK: The story inside big firms will be complicated, I think. At Procter & Gamble, we did an experiment with 776 of their employees. They either were technical or business people, and they either worked individually or on teams of two. The finding at the time was individuals using A.I. performed as well as teams not using A.I. To me, the really interesting part was that it also blurred lines between roles. Business people used to have business ideas, tech people came up with technical ideas. But add A.I., and everyone comes up with ideas in between each other. And that’s happening everywhere. When I talk to people in coding, especially in industries that have some quasi-creative element, like the gaming industry, suddenly the people who are designers can code, suddenly the coders can do design work, the artists can start writing.
