Big Tech, You Need Academia. Speak Up!

"It is unlikely that Elon Musk reads Communications. Even if I send him a copy of this column, will it change his mind?" In this edition of "Advances in Computing," ACM Fellow and former CACM Editor-in-Chief Moshe Vardi makes a compelling case for the continued relevance of academic computing research.

Also featured: two articles on the future of programming in the age of artificial intelligence, a call to invest in technologists at all levels of government, and hand-picked stories from Interactions, ACM's magazine on user experience and interaction design.

Enjoy!

The current U.S. administration has launched a war on academia. On Feb. 7, 2025, the U.S. National Institute of Health announced a 15% limit on indirect research costs for new and existing grants. Indirect costs, or, more accurately, facility and administration expenses, support research but cannot be directly attributed to a specific project, such as lab infrastructure, utilities, and administrative support. These are real costs; the limit, which has since been suspended by courts, is a severe blow to biomedical research in the U.S....

Big Tech may dismiss these concerns regarding the future of U.S. academic computing research. After all, Big Tech consists of six corporations with more than US$1 trillion in market capitalization each; their research budgets dwarf governments research budgets in computing. Furthermore, industrial researchers have access to large-scale data and computing that academic researchers can only dream of. While the NSF’s Directorate for Computing and Information Science and Engineering has an annual budget of about US$1 billion, DeepMind, a subsidiary of Alphabet focusing on AI research, has an annual budget of around US$2 billion.

But dismissing academic computing research as irrelevant, given the size of Big Tech, would be a grave mistake. As I argued in 2019, research is a long game. Consider the current wave of generative AI. While this wave, going back to the mid-2010s, is driven almost exclusively by industrial research, it builds on a 70-year academic effort in neural computing. We must remind ourselves of the concerns of Abraham Flexner, founder of the Institute for Advanced Study in Princeton. In The Usefulness of Useless Knowledge, Flexner explored the dangerous tendency to forgo pure curiosity in favor of alleged pragmatism....

As evidence for the value of curiosity-driven research in computing, I offer the Tire-Tracks Diagram, a graphical illustration of how federally funded university research and industrial research and development precede the emergence of large IT industries by decades. The diagram shows eight technologies whose values have surpassed USD$1B. From the eight technologies, only one clearly traces its birth to industrial research (relational databases.)

Research-intensive academic departments, however, produce more than just original ideas. Generally, academic research is carried out by doctoral students, supervised by faculty members, and supported mostly by federal funding. According to the CRA Taulbee Survey, in 2023 U.S. computer science (CS) departments graduated 1,883 doctorate holders, from which 870 went to industry. Obviously, industry values people who can formulate and solve problems. Doctorate holders play a key role in tech; case in point, Amazon’s Automated Reasoning Group. The most notable example, however, is Google, which was founded by Sergey Brin and Larry Page—two CS doctoral students at Stanford University.

It is unlikely that Elon Musk reads Communications. Even if I send him a copy of this column, will it change his mind? I am not sure. Perhaps, however, he would listen to his fellow Big Tech CEOs. Big Tech, you need academia. Please speak up!

Visit the full article here.

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