New Study Offers Reassurance on AI and Jobs

The International Labor Office took a look at how AI might change human work patterns in the future. Focusing on Chat GPT-4, the study determined that clerical work is likely to go the way of the dinosaurs. 24% of the tasks can just be taken over directly by generative AI tools, and another 58% of the tasks will be “exposed” to automation with these tools.

Since women are disproportionately represented in clerical work, the ILO is expecting that women’s livelihood will be most threatened. In fact, women are twice as likely to be out of a job as men.

Outside of clerical work, however, the percentage of tasks that can be taken on entirely by AI will generally be less than 5%, with no more than 25% exposure. AI, they conclude, will generally augment rather than automate most human jobs outside of the clerical sphere.

Jobs or tasks

The study looked at ten different types of jobs, from managers to skilled agricultural/forestry/fishery workers, and including military jobs and machine operators. Within these jobs, they identified 4,360 tasks.

Chat GPT helped with the work of listing the tasks and gave its own views on whether it could help. For example, it said that it could create lesson plans but that human teachers were essential for children. This was in part “because human interaction and physical presence are essential for effective discipline and enforcing rules.”

Chat GPT also felt that it wouldn’t be great at attending meetings and collaborating with other teachers.

Having Chat GPT give its own opinions on its capacity works better, the report, says, because “tech experts tend to overstate technological capacities and risks in questions concerning broader applications.” The ILO gave the example of garment construction, which human beings tend to think robots with AI will be able to do. In practice, robots are no good at sewing. They are generally not able to sew garments, and what they can do is slower and more expensive than human work.

Many jobs in manufacturing have high potential for augmentation — that is, using generative AI to make work more efficient — rather than for outright automation.

Now what?

“[T]he main value of studies such as this one is not in the precise estimates, but rather in understanding the possible direction of change,” says the ILO. “Such insights are necessary for proactively de- signing policies that can support orderly, fair, and consultative transitions, rather than dealing with change in a reactive manner.”

The final section of the report gives ideas for an orderly transition from mostly human workers to largely AI workers. They favor training and redeployment, and suggest a future in which employers work with human employees to minimize job loss.

They would like to see displaced workers diverted to “the care economy” of health care and education, which they feel are underfunded as well as likely to require human workers. They are also concerned about AI management of human work, seeing negative possible outcomes from management by algorithm.

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