Can AI Make Scientific Breakthroughs? - Cosmos Institute
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Can AI Make Scientific Breakthroughs?<br>Tacit Knowledge is Essential for Discovery
Cosmos Institute<br>Jul 03, 2026
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This essay is by Iulia Georgescu, a physicist and independent scholar researching the history of computational physics, and Venkatesh Narayanamurti, Emeritus Professor of Technology and Public Policy, Engineering and Applied Sciences and Physics at Harvard University.
View of Cotopaxi, Frederic Edwin Church (1857)<br>In May 1825 Johann Peter Eckermann transcribed his conversation with Johann Wolfgang von Goethe which was later published in the book Gespräche mit Goethe. An excerpt from the exchange between the two poets is the popular quote: “It is by seeking and blundering that we learn.”<br>While the aphorism represents a piece of wisdom that resonates with many of us, the forgotten context is somewhat unexpected. Rather than articulating a deep philosophical insight, Goethe was in fact commenting on Eckermann’s knowledge of the best types of wood and most appropriate techniques for crafting a good archery bow.<br>Goethe referred to Eckermann’s expertise as “the lively kind of knowledge which is attained only in a practical way.” Today we call it tacit knowledge, which despite being notoriously difficult to define and quantify, plays an essential role in advancing the frontiers of scientific research.<br>A narrow, yet increasingly popular, view of research is the following: read scientific papers, generate hypotheses, test them, write more papers. The appeal this picture has for AI companies, funders and publishers is clear: research is easy to automate, outputs are easy to quantify and monetize (with automation more articles can be produced and published). While the latter is certainly true and there is a deluge of AI-generated scientific articles, many of dubious quality), the automation of research has not yet produced any major breakthroughs.<br>If large language models have ingested most of the scientific literature which can now be parsed in ways no individual or collective of human researchers could in their lifetimes, why is it that no ground-breaking discoveries have yet emerged?<br>First, the read-generate-hypothesis-test-write view is not how research works in practice. As other creative human activities, research is a social, complex and often inefficient process that is hard to describe through a linear sequence of block diagrams.
Second, the scientific textual record is only part of the story. The other part is transmitted through oral tradition and lived experience and is key to making progress.
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Embodied knowledge or deep craft?
To define tacit knowledge, we need to first acknowledge that science cannot be decoupled from the technology which enables it, be it a 19th century microscope or a 21st century supercomputer. The technoscientific method introduced in the 2021 book The Genesis of Technoscientific Revolutions proposes that “science draws on technology to discover new facts, while technology draws on science to invent new forms with which to fulfil human-desired functions.” From this perspective technoscientific knowledge consists of networks of question-answer pairs that are combined and evolved into new pairs expanding the domain of what is known.<br>Philosopher Sabina Leonelli identified three types of epistemic skills that underpin research and specific knowledge associated with these, namely: theoretical (such as as facts, theories, explanations) and embodied knowledge (the awareness of how to act and reason as required to pursue scientific research, combining the application of performative and social skills). Similar ideas have been articulated before, for example by Michael Polanyi (1958) who referred to it as the tacit component in the context of ‘personal knowledge’.<br>Following Polyani, Thomas Kuhn stressed on the importance of tacit knowledge in skilled scientific practice. In his 2009 book, economist W. Brian Arthur called it deep craft:<br>“Deep craft is more than knowledge. It is a set of `knowings’. Knowing what is likely to work and what not to work. Knowing what methods to use, what principles are likely to succeed, what parameter values to use in a given technique. Knowing whom to talk to down the corridor to get things working, how to fix things that go wrong, what to ignore, what theories to look to.”
These definitions of tacit knowledge have two things in common: there is an embodied-performative dimension (the “lively kind of knowledge” Goethe suggested can only be attained in a practical way) and a social dimension (through the scientific culture of the discipline and the social network of its practitioners). Tacit knowledge is not only associated with experimental practice. Sociologist Harry Collins noted that “all types of knowledge, however pure, consist, in part, of tacit rules which may be impossible to formulate in principle.”<br>To some extent tacit...