Better-Paid, White-Collar Jobs Most Threatened By AI

In a recent Brookings Institution report, authors Mark Muro, Jacob Whiton and Robert Maxim make the case that better-paid, white-collar professionals are most at risk of losing their jobs to artificial intelligence.

As the report points out, past studies have had little actual data to go on and have, instead, relied on case studies and subject assessments to predict which jobs and industries were most vulnerable.

“What’s more, most research has concentrated on an undifferentiated array of ‘automation’ technologies including robotics, software, and AI all at once,” the report says. “The result has been a lot of discussion—but not a lot of clarity—about AI, with prognostications that range from the utopian to the apocalyptic.”

In contrast, a new method devised by Stanford University Ph.D. candidate Michael Webb compares job descriptions with AI-related patents, giving a higher degree of accuracy.

The new data shows that low-wage jobs will continue to be heavily impacted by automation and robotics. When it comes to true AI, however, “the present analysis suggests that better-educated, better-paid workers (along with manufacturing and production workers) will be the most affected by the new AI technologies, with some exceptions.”

Professions that have a high amount of predictive work, or pattern-oriented tasks are the kind of jobs AI is particularly well-suited to take over.

“At the high end of AI involvement, for example, are numerous well-paid occupations that had relatively low exposure in our earlier, all-encompassing automation analysis. They range from market research analysts and sales managers to programmers, management analysts, and engineers. Often analytic or supervisory, these roles appear heavily involved in pattern-oriented or predictive work, and may therefore be especially susceptible to the data- driven inroads of AI, even though they seemed relatively immune in earlier analyses.”

In addition, individuals “with graduate or professional degrees will be almost four times as exposed to AI as workers with just a high school degree.” The data also shows that high-tech metro areas will be more susceptible than most rural areas.

The original, in-depth report is 46 pages long and is a fascinating read, providing some all-new insights into the far-reaching impacts AI will have on all economic sectors.

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