Artificial intelligence expected to have a big impact on white collar jobs

Better educated, better paid white collar workers will be the most affected by artificial intelligence (AI), according to a newly released report by the Brookings Institution. The report goes against previous findings of Brookings’ and other research that shows less educated and lower-wage workers will be most impacted by robots. 

Stanford University researcher Michael Webb’s approach was to take the text of patents to identify the capabilities of AI, and then quantify the extent to which each occupation involves these technologies. Webb used natural language processing to quantify the overlap between patent texts and job description text and came up with an exposure score for each job.

SEE: Special report: Managing AI and ML in the enterprise (free PDF) (TechRepublic)

Out of the 769 occupational descriptions Webb analyzed, 740 “contain a capability pair match with AI patent language, meaning at least one or more of its tasks could potentially be exposed to, complemented by, or completed by AI,” the report noted. “Importantly, this does not mean such tasks will be broadly replaced and result in work loss.”

Defying earlier analyses

Well-paid occupations ranging from market research analysts and sales managers to programmers, management analysts, and engineers, which are often analytic or supervisory roles “may,” the Brookings Report said, “be especially susceptible to the data-driven inroads of AI, even though they seemed relatively immune in earlier analyses.”

Other jobs that may be AI targets are agriculture and manufacturing positions.

“Whereas our and other’s work has shown that less-educated, lower-wage workers appear most exposed to potential disruption from robotics and software, Webb’s AI exposure estimates, and our analyses here suggest the opposite pattern: Better-educated, better-paid workers will be the most affected by the new technology, with some exceptions,” the report said. 

Brookings explains that because AI technologies have not yet been widely adopted, analyses such as its own “or those from Oxford, OECD [The Organisation for Economic Co-operation and Development], and McKinsey have had to rely either on case studies or subjective assessments by experts to determine which occupations might be susceptible to an AI takeover.”

By contrast, several low-paying, rote jobs involving hands-on services such as in personal care, food preparation, or healthcare “will be relatively unexposed to changes from AI applications, at least for now.” Most notably, accommodation and eating/drinking services, and retail now join the health and education industries as being relatively immune to AI, according to the report.

In terms of specific service sectors, the report found that “high-tech digital services such as software publishing and computer system design—that before had low automation susceptibility—exhibit quite high exposure, as AI tools and applications pervade the technology sector,'” such as robotic process automation. 

Men are also targets

AI is also expected to impact men, who are overrepresented in analytic-technical and professional roles and received much higher AI exposure scores than women, according to the report.

“Women’s heavy involvement in ‘interpersonal’ education, healthcare support, and personal care services appears to shelter them,” the report noted.

Age is also a factor. “Prime-age” workers ranging from 25 to 54 are employed in occupations that are going to be disproportionately involved with AI. Surprisingly, Webb’s exposure pattern differed sharply from previous automation analysis, which found that young workers (ages 16 to 24) faced the highest automation risks given their heavy overrepresentation in low-skill food preparation jobs, the report said.

In the case of AI, however, exposure scores peak in midcareer, where professional and technical workers at this level are likely to be the prime targets of AI, the report said.

In terms of demographics, “AI looks most destined to affect men, prime-age workers, and white and Asian American workers,” the report said. This is because white and Asian American workers are heavily overrepresented in technology, engineering, and legal-managerial occupations, according to the report, ensuring “both groups will be impacted most by the arrival of AI.”

Conversely, AI is less likely to affect black and Latino or Hispanic workers given their overrepresentation in occupations such as personal care work, facilities maintenance, and community and social services occupations. Those professions are all projected by Brookings to have low AI exposure in the coming years.

AI’s impact by state, metro areas

Nevada went from being one of the most “exposed states” to one of the least, while Washington state “has moved in the other direction and is highly exposed to AI,” likely because of its specializations in advanced manufacturing and technology in and around Seattle.

Among the most AI-exposed large metro areas are: San Jose, Calif.; Seattle; Salt Lake City; and Ogden, Utah—all high-tech centers—along with agriculture and logistics hub Bakersfield, Calif.; and manufacturing centers Greenville, S.C.; Detroit; and Louisville, Ky.
The five least exposed metro areas are: El Paso, TX; Cape Coral-Fort Myers, FL; Las Vegas-Henderson-Paradise, NV; Deltona-Daytona Beach-Ormond Beach, FL: and McAllen-Edinburg-Mission, TX.

The report concludes that AI is a much different technology than earlier types of automation and will affect a very different part of the workforce than previously thought.

“AI will be a much greater factor in the future work lives of relatively well-paid managers, supervisors, and analysts (as well as production workers, who are increasingly well educated in many occupations as well as heavily involved with AI on the shop floor),” the report said. “It may be much less of a factor in the work of most lower-paid service workers.”

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