HAI executive director calls for reform in academia to stay competitive with private companies
According to Russell Wald, Executive Director for Stanford’s Institute for Human-Centered Artificial Intelligence (HAI), academia needs reform in order to stay in the “AI game.”
Wald elaborated on the topic in conversation with both undergraduate and graduate students at a seminar held at the Gates Compute Science Building on Jan. 15, revolving around academia’s role in AI. Wald, who has been at Stanford for over a decade, argued that there is a current trend in academia away from competitive participation in AI research.
The private sector is dominating AI development at an inconceivable pace, something that could be difficult to ameliorate if government-investing remains vacant, Wald said. Perhaps most interestingly, industry has risen to the top of AI research efforts because companies like Google, Meta and OpenAI dominate talent acquisition, resulting in the augmentation of their already-competitive AI expansion. In turn, these companies amass a disproportionate amount of funding which prevents government and civil society from contributing to the development of AI systems.
With others turning to entrepreneurship, Wald said that 20% of Ph.D. candidates studying AI go into academia while around 70% migrate towards industry sectors. The concept of “brain drain” has also become concerning in recent years as tenured professors at academic institutions are relinquishing their positions to enter industry seats, a phenomena that could be troubling when trying to train the next generation of pioneers in AI. A study released by the New York Times revealed that in 2019, 153 professors left their posts for industry. In 2025, the rate at which professors are leaving academia for industry is likely much higher.
“[AI will] permeate into everything we do, eventually. Kind of like the internet,” Lillian Weng M.S. ’26 said after the seminar in an interview with The Daily. The consequences of an industry-dominated AI environment may have unfavorable effects on the future of innovation in AI, especially for academic institutions.
Other students said they are also thinking about the way that AI will interject itself into other disciplines, like medicine. “AI has already begun to bleed into the patient-physician interface,” said Pedro De La Torre ’27, who is studying neurobiology. “A professor of mine mentioned the use of software that consistently omits humanistic traits during patient-consultation. It’s efficient, but can be dangerous if used incorrectly.”
Wald suggested that AI research has taken on a lack of transparency in recent years and encouraged the U.S. government to continue investing in public sector AI. The seminar concluded with the idea that governments must reform in order to gear AI research in the direction of public interest.
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