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What stories should we tell about science now? - mklabgr - 08-30-2026
Summary
In this essay, Jessica Hullman reflects on the changing role of universities and academic science at a moment when U.S. research institutions face funding cuts, declining graduate enrollment, tighter visa policies, and a migration of researchers—especially in AI and computer science—toward industry. She questions the traditional postwar “social contract for science,” according to which society gives scientists public funding and intellectual freedom because basic research eventually feeds technological and economic progress. Drawing on philosopher Heather Douglas, Hullman argues that the familiar distinction between “basic” and “applied” science is much less clear than it appears: applied work can generate fundamental discoveries, while apparently pure research can quickly become useful. AI illustrates this ambiguity particularly well, since major advances such as transformers, scaling laws and AlphaFold emerged largely from industry, even though they depended heavily on decades of academic research.
Hullman nevertheless argues that the lesson should not be that universities have become unnecessary. Academic institutions provide things that commercial research environments may struggle to preserve: intellectual autonomy, time for deep investigation, tolerance for ideas without immediate profitability, training in scientific judgment, and the possibility of exploring research directions outside the dominant assumptions of powerful companies. This matters especially in AI, where enormous financial resources are concentrated in a few firms that can effectively determine which research questions appear important. At the same time, Hullman rejects the romantic idea that academic science is automatically morally superior: scientific autonomy can also become insulation from social responsibility, and simply increasing our ability to predict, manipulate or control the world does not necessarily constitute genuine human progress.
Her central conclusion is therefore that defending “academia” or “basic science” as categories is probably the wrong argument. What society should defend are the conditions that make good science possible: time, independence, scientific training, intellectual diversity, and institutions capable of evaluating discoveries independently of their profitability. Scientific progress cannot be measured merely by technological capability; society must also judge whether new capabilities are desirable. Universities and independent research institutions remain valuable partly because they can provide an intellectual counterweight to governments and corporations and help society decide not merely what science can do, but what science ought to do.
Key takeaways
- The traditional basic science → applied science → innovation model is historically influential but overly simplistic.
- Industry's success in AI does not prove academic research is dispensable; today's breakthroughs rest partly on decades of university research.
- The strongest justification for universities may be intellectual autonomy and independent scientific judgment, rather than promises of specific economic returns.
- Scientific progress should not mean merely greater predictive or technological power; society must also evaluate whether that power produces desirable outcomes.
ARTICLE