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Radium is an element,” the chemist Marie Curie once told an interviewer. “It belongs to the people.” This was ironic since in that same interview, Curie—the first woman to win a Nobel Prize, and the first person to win it twice—explained that she didn’t have the funding to continue her work on radium. “I need a gram of radium to continue my researches,” she explained, “but I cannot buy it. Radium is too dear for me.”
Marie Curie’s research, and that of her husband, Pierre Curie, led to incredible advances in nuclear science. Despite the tremendous practical usefulness of their research—such as paving the way for radiation therapy in cancer treatment—the Curies did not patent any inventions. As a result, they never saw significant profits from their discoveries. Their story illustrates the idea, developed by the sociologist of science Robert Merton, that academic scientists are communists. At the very core of scientific knowledge production in the academy is a rule that researchers do not keep their findings secret. They share discoveries widely and freely—including to those who might someday profit off of them.
This creates a problem. While industry researchers have free access to academic work, academic scientists typically cannot use industry findings in their own research. A 2022 report estimated that United States businesses spent $485 billion on research and development, nearly three quarters of total U.S. research expenditures. But advertising firms and pharmaceutical companies don’t pay for research so they can share their findings widely.
Scientific communism creates direct profits for capitalist entities.
It may seem perfectly fine for industry to keep their own research proprietary. But the problem is that science is cumulative. It builds off past work. Industry research relies heavily on discoveries from academic science, over half of which is funded by the U.S. government. The public pays for academic research, but private corporations reap many of the rewards.
Philosopher of science Jingyi Wu uses network models to reveal some of the pernicious effects of this asymmetry. She looks at cases where one sub-group of scientists keeps their data private while still learning from all the data other scientists produce. In other words, she models the relationship typical of industrial and academic research. In her dissertation, Wu shows that the sub-group who does not share their data tends to learn better and faster than the one that does. This is in part because they get more information about the problem. Crucially, though, they also learn better because the “academic” group gets less information. When researchers receive less data, they tend to learn more slowly, and take more time exploring various possible solutions to the problem. The non-sharers, meanwhile, can learn from this exploration while exploiting the best current information.
There are many cases where scientific progress would benefit immensely from proprietary knowledge. In my own work on misinformation, it would be extremely helpful to view proprietary findings from advertisers on online influence. I’ve spoken to linguists who want to get their hands on data from companies responsible for online hate speech detection; academics who want to know about microgravity research performed by private companies on the International Space Station; and a biomedical researcher who wants to see whether pharma researchers have successfully replicated various findings in drug development.
Wu uses simple models to make this point, but the central observation is a general one—industry can learn and profit from academic findings, but academic researchers are often unable to learn from industry. Scientific communism creates direct profits for capitalist entities.
What should be done about this? In a 2023 paper, Wu and I argue that there should be some sort of requirement for industry to share proprietary research, given that much of this research “stands on the shoulders” of publicly funded work. The trick, of course, is that businesses often fund research for the very reason that they then get to keep profits from the findings. Requirements to share might interfere with incentives to produce research in the first place.
While it might not be easy to implement better sharing rules for industry research, public good and fairness dictate that we take this mandate seriously. When industry takes advantage of scientific communism, we should all benefit. 
Lead image: ProStockStudio / Shutterstock
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