AI won't take our jobs and it might even save the middle class

MIT economist argues ML can moderate the inequalities of the Information Age

The future described in OpenAI's mission statement, in which autonomous systems "outperform humans at most economically valuable work," sounds like a hellscape to MIT economics professor David Autor.

A world where humans supply only generic, undifferentiated labor and wealth flows to AI system owners and rights holders would look something like "WALL-E" meets "Mad Max," he says.

But it doesn't have to be that way. In an paper released through the National Bureau of Economic Research, "Applying AI to Rebuild Middle Class Jobs," Autor argues that fears of a future in which AI will leave humans with nothing to do are misplaced and in fact, AI can improve the lot of the middle class.

Citing Elon Musk's prediction during a recent interview with UK Prime Minister Rishi Sunak that "...there will come a point where no job is needed," and AI pioneer Geoffrey Hinton's advice to "get a job in plumbing," Autor argues the future will not lack jobs. Declining birth rates and a shrinking labor force, he contends, will ensure a labor shortage.

The question is more centered on what available jobs will entail. Autor believes that the emergence of AI as an assistive tool provides a path to undo the damage of the Information Age, which has devalued the procedural expertise of middle class workers and shifted power to elite decision makers.

"The unique opportunity that AI offers humanity is to push back against the process started by computerization – to extend the relevance, reach and value of human expertise for a larger set of workers," he writes.

"Because artificial intelligence can weave information and rules with acquired experience to support decision-making, it can enable a larger set of workers equipped with necessary foundational training to perform higher-stakes decision-making tasks currently arrogated to elite experts, such as doctors, lawyers, software engineers and college professors."

If you're a highly paid professional in a credential-gated profession, this may not sound like the ideal outcome. But there is precedent for such shifts.

For example, Autor cites the job of Nurse Practitioner, who are Registered Nurses (RNs), with an additional master's degree that certifies them to perform tests and administer services previously reserved for physicians.

The number of Nurse Practitioners in the US, he notes, nearly tripled between 2011 and 2022 to roughly 224,000 and that number is expected to grow 40 percent over the next decade. What made that possible? Beyond the decisions by medical professionals back in the 1960s to use the skills of registered nurses more effectively and to change medical regulations, Autor points to information technology, specifically electronic medical records.

"Electronic medical records and improved communication tools enabled NPs to make better decisions," Autor writes, and he argues that AI can similarly empower other workers to make decisions that would otherwise be left to experts.

He points to several studies of the impact that GitHub's Copilot and OpenAI's ChatGPT have had on computer programming and writing tasks respectively. Neither eliminated the need for expertise but both helped make less workers more productive.

"Artificial Intelligence is this inversion technology," Autor insists. "By providing decision support in the form of real-time guidance and guardrails, AI could enable a larger set of workers possessing complementary knowledge to perform some of the higher-stakes decision-making tasks currently arrogated to elite experts like doctors, lawyers, coders and educators."

AI, he says, can improve the quality of jobs for those without college degrees, reduce earning inequality, and lower the cost of healthcare, education, and legal advice, just as the Industrial Revolution made consumer goods more affordable.

Autor makes clear he doesn't anticipate AI eliminating the need for expertise. It won't, he says, let untrained people perform skilled tasks like catheterization. But it will let workers with some foundation in a task level up.

This outcome, Autor says, is not inevitable. "It is, however, technologically plausible, economically coherent and morally compelling," he concludes. "Recognizing this potential, we should ask not what AI will do to us, but what we want it to do for us." ®

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