Where Did All the Computer-Science Professors Go? - The Atlantic

Anthropic has poached such an array of high-profile professors that it has become a punch line in academia. “‘I’m joining Anthropic’ is the new meme right now,” Subbarao Kambhampati, a computer-science professor at Arizona State University (who has not joined Anthropic), told us. This month, the AI company hired the chair of UC Berkeley’s department of electrical engineering and computer science, presumably to help build more capable bots. Perhaps more surprisingly, Anthropic has in recent weeks also picked up a Stanford economist, a theoretical physicist from the University of Maryland, and an analytic philosopher from UT Austin.

AI companies are turning into something like mini-universities in their own right. OpenAI employs top mathematicians and physicists—including one who studies black holes, and another who specializes in string theory. At least three computer-science professors joined Meta’s AI lab in late June. DeepMind, like Anthropic, is home to a crew of philosophers. And Anthropic’s recent job postings indicate an interest in hiring legal scholars and political scientists. It’s unclear exactly how many current and former professors are working at AI companies. Across these four firms, we found more than 80—the majority of whom are computer scientists. Some have left academia entirely; others are still working part-time at a university. That number is likely a significant undercount, because we don’t have access to internal data; it also doesn’t include the many professors who have started their own companies, those at other AI start-ups, and those working with the industry in a less formal capacity.

Particularly for AI researchers, these companies have a strong gravitational pull. “Much of the important research is being done in industry now,” Humphrey Shi, a computer-science professor at Georgia Tech who joined Nvidia as a vice president last fall, told us. As he sees it, “If you want to do something that really, truly matters, you probably want to join one of those entities.” Tech firms are making offers—including very enticing salaries—that are hard for academics to refuse. In the process, research that previously would have happened in the open is getting locked up behind closed doors.

For decades, universities were the center of AI research. The field itself officially began at a gathering of researchers at Dartmouth in 1956, and federal funding provided much of the field’s early support. In the early 2010s, Silicon Valley executives began to take AI’s commercial potential more seriously, and set out to hire the best researchers. In 2013, Google paid $44 million to acquire a start-up run by a trio of AI researchers from the University of Toronto. Facebook then hired Yann LeCun, an NYU professor, to establish the company’s AI-research lab; Uber poached some 40 Carnegie Mellon researchers to work on driverless cars. But for the most part, even as more work was being done inside of private companies, many of the newly hired academics at tech companies retained their professorships and established a culture of open research. “Researchers will be strongly encouraged to publish their work,” OpenAI wrote in its founding announcement. (Note the organization’s name.) This norm helped lead to the current AI boom: In 2017, scientists at Google published a research paper that was immediately of interest to OpenAI. Google’s innovation, called the “transformer,” is what the T in ChatGPT stands for.

As AI has taken center stage, Silicon Valley has intensified its efforts to recruit star researchers—and looked beyond computer-science departments. Philosophers help train tech companies’ bots to better interact with humans, and economists study the labor-market implications of AI. Compensation is only part of the draw. The current era of AI research requires massive amounts of computing power. Universities have only a fraction of the resources that Silicon Valley can provide, and the chasm has widened as the Trump administration has cut back on scientific funding. Anca Dragan, a UC Berkeley computer scientist who heads DeepMind’s AI-safety-and-alignment department, wrote to us that she was partly motivated to take the job to acquire “the data, compute, and budget access to make progress on safety at the frontier.” Some professors who remain in academia are also forming partnerships with frontier labs or starting their own AI companies, in part so that they can pursue their research without resource constraints. And in some cases, would-be star Ph.D. students are dropping out of their graduate programs—or skipping them altogether—to pursue careers in AI instead.<br>Read: Someone finally wants to hire philosophers<br>Although plenty of research is still happening within universities, many professors told us, the result is a flywheel: As more academics get sucked up by industry, the center of AI research moves further from academia, thus...