In the first two dimensions, the AI enables humans to gain new scientific understanding, whereas in the last, the machine gains understanding itself. Although there have not yet been any examples of AI acting as a true ‘agent of understanding’ in science, we outline important characteristics of such a system and discuss possible ways to achieve it. AI reaches new scientific insight and - importantly - can transfer it to human researchers. Third, AI acts as an agent of understanding. Second, AI can act as a source of inspiration for new concepts and ideas that are subsequently understood and generalized by human scientists. Humans then lift these insights to scientific understanding. ![]() In this way, we are focusing on the operational objective rather than the methodology.) First, AI can act as an instrument revealing properties of a physical system that are otherwise difficult or even impossible to probe. (We encapsulate all advanced artificial computational systems under the term AI, independent of their working principles. We then identify three fundamental dimensions for AI contributing to new scientific understanding (Fig. We discuss the literature overview and personal accounts in the context of the philosophical theory of scientific understanding recently developed by Dennis Dieks and Henk de Regt 12, 13. These personal narratives (see Supplementary Information) focus on the concrete discovery process of ideas and are a vital augmentation of the scientific literature. ![]() In addition to the review of the literature, we surveyed dozens of scientists working at the interface of biology, chemistry or physics on the one hand, and AI and advanced computational methods on the other. ![]() In this Perspective, we discuss how advanced computational systems, and AI in particular, can contribute to scientific understanding: we overview what is currently possible and what might lie ahead. Some have questioned whether advanced computational approaches can go beyond ‘numerics’ 5, 6, 7, 8, 9 and contribute on a fundamental level to gaining of new scientific understanding 10, 11, 12. However, this excitement has not been shared by all scientists. In the context of theoretical chemistry, for example, it is believed that AI can help solve problems “in a way such that the human cannot distinguish between this and communicating with a human expert” 4. We hope that this Perspective will inspire and focus research directions in this multidisciplinary emerging field.Īrtificial intelligence (AI) has been called a revolutionary tool for science 1, 2 and it has been predicted to play a creative role in research in the future 3. For each dimension, we review the existing state of the art and discuss future developments. With the increase in the available computational power and advances in artificial intelligence, a natural question arises: how can advanced computational systems, and specifically artificial intelligence, contribute to new scientific understanding or gain it autonomously? Trying to answer this question, we adopted a definition of ‘scientific understanding’ from the philosophy of science that enabled us to overview the scattered literature on the topic and, combined with dozens of anecdotes from scientists, map out three dimensions of computer-assisted scientific understanding. This is scientific understanding, one of the main aims of science. However, scientists would not be entirely satisfied because they would want to comprehend how the oracle made these predictions. ![]() An oracle that correctly predicts the outcome of every particle physics experiment, the products of every possible chemical reaction or the function of every protein would revolutionize science and technology.
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