Colleges Race to Hire and Build Amid AI ‘Gold Rush’
![Colleges Race to Hire and Build Amid AI ‘Gold Rush’](https://www.educationaladvisors.com/app/uploads/2023/04/IHE-e1681148960886.jpg)
Inside Higher Ed
Susan D’Agostino
May 19, 2023
OpenAI’s release of ChatGPT in late 2022 launched an artificial intelligence arms race among Google, Microsoft and countless other tech giants and start-ups. That development has since reverberated across higher ed, unleashing a surge of new faculty hires, buildings and institutes—all for AI.
The University at Albany, part of the State University of New York, will hire 27 new faculty members—all specializing in AI—in the largest cluster hire in the institution’s history. Purdue University will recruit 50 new AI faculty. Emory University will hire between 60 and 75 new faculty members, including an endowed chair, for its AI Humanity Initiative.
When it comes to artificial intelligence, some universities are going big—very big. The University of Southern California has invested more than $1 billion in its AI initiative that will include 90 new faculty members, a new seven-story building and a new school. The institution seeks to bolster its economic impact in the tech industry, integrate computing across multiple disciplines and programs at the university, and influence AI applications, development, policy and research.
“It’s a gold rush,” Phil Hill, an educational technology market analyst at Phil Hill and Associates, said. “But it’s a gold rush where you don’t know where the gold mine is or how to get the gold.”
Many, though not all, of the new faculty hires will be computer scientists, which presents challenges given recent shortages in this area. Also, once AI faculty are hired, colleges will need to identify creative ways to retain them, given their red-hot demand in both academe and industry.
Most academics agree that the current AI moment marks a profound societal shift that warrants a higher ed overhaul. But as college leaders cue bulldozers to build institutes that will house hordes of new AI professors, some offer reminders that hype, even when warranted, does not always follow a predictable trajectory. Further, significant change often includes pain points.
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