“It does seem to be doing something fundamentally different,” said David Autor, another M.I.T. economist, who advises Ms. Zhang and Mr. Noy. “Before, computers were powerful, but they simply and robotically did what people programmed them to do.” Generative artificial intelligence, on the other hand, is “adaptive, it learns and is capable of flexible problem solving.”
That’s very apparent to Peter Dolkens, a software developer for a company that primarily makes online tools for the sports industry. He has been integrating ChatGPT into his work for tasks like summarizing chunks of code to aid colleagues who may pick up the project after him, and proposing solutions to problems that have him stumped. If the answer isn’t perfect, he’ll ask ChatGPT to refine it, or try something different.
“It’s the equivalent of a very well-read intern,” Mr. Dolkens, who is in London, said. “They might not have the experience to know how to apply it, but they know all the words, they’ve read all the books and they’re able to get part of the way there.”
There’s another takeaway from the initial research: ChatGPT and Copilot elevated the least experienced workers the most. If true, more generally, that could mitigate the inequality-widening effects of artificial intelligence.
On the other hand, as each worker becomes more productive, fewer workers are required to complete a set of tasks. Whether that results in fewer jobs in particular industries depends on the demand for the service provided, and the jobs that might be created in helping to manage and direct the A.I. “Prompt engineering,” for example, is already a skill that those who play around with ChatGPT long enough can add to their résumés.
Since demand for software code seems insatiable, and developers’ salaries are extremely high, increasing productivity seems unlikely to foreclose opportunities for people to enter the field.
That won’t be the same for every profession, however, and Dominic Russo is pretty sure it won’t be true for his: writing appeals to pharmacy benefit managers and insurance companies when they reject prescriptions for expensive drugs. He has been doing the job for about seven years, and has built expertise with only on-the-job training, after studying journalism in college.