Make science disruptive again. Itai Yanai & Martin J. Lercher. Nature Biotechnology (2023)
The rate of scientific innovation appears to be slowing down: despite immense investments, the proportion of individual projects that push science in new directions by breaking with previous understanding has decreased since the 1950s1. Some observers have attributed these diminishing returns to the notion that fewer fundamental discoveries remain to be made2. But a compelling case can be made for another factor: that the culture of science has gradually transitioned toward a more executive and results-oriented approach. In this fast-paced mode, scientists and scientists-in-training — graduate students and postdoctoral fellows — have little time for more exploratory topics, which contributes to a less creative environment for transformative science. This trend may have been fortified by science becoming increasingly entrenched into siloed disciplines3 and by projects being progressively dominated by hypothesis-driven approaches4, fueled by a spirit of strategic design that emphasizes predictability rather than unexpected results.
As a tangible first step toward changing this culture, we suggest that graduate study programs should renew an emphasis on creativity by teaching the tools of innovative thinking5.
Over the past 4 years, we have been promoting a discussion on the creative side of the scientific process in editorials6, podcast episodes7 and workshops5. At the core of our approach is a distinction between two complementary aspects of science, which François Jacob has referred to as ‘day science’ and ‘night science’8,9. While day science is the executive domain, in which we test specific hypotheses by implementing tools and designing experiments, it is useful to distinguish a separate night science domain that creates the questions, makes connections to seemingly distant concepts and explores new directions. Journals and conferences focus exclusively on day science, and for good reasons: only with empirical evidence can we settle scientific disagreements, and that is the realm of day science10. Accordingly, current graduate programs teach the day science skills that are required for experimental design, grant writing and science communication through manuscripts and presentations. By contrast, they typically lack any explicit training on how to be scientifically creative and how to develop new ideas in the first place. Without structured learning on the distinct sets of skills required for the executive day-science and creative night-science spheres, science education remains incomplete.
In discussions, some of our colleagues have suggested that with regards to creativity, ‘you either have it or you do not’. But this view contradicts a substantial body of creativity research, which asserts that we each have innate creative skills that we can learn to access better and more efficiently11,12. Indeed, creativity training is well established in the arts and entrepreneurship, and many general approaches can be transferred to a science curriculum. In the sciences though, creativity operates under very different constraints. Science education will be more efficient if it recognizes these differences and focuses on creative approaches that are widely used by practicing scientists. First and foremost, a course on creativity would recognize that the complete scientific process consists of a tight interplay between executive and exploratory activities, with the night science domain providing a sandbox for creative explorations that can then be brought to the day science sphere to test their validity. Students would learn to appreciate that research projects rarely proceed as expected, and that unexpected developments and discoveries typically evolve from an unpredictable interplay between questions and data.
Beyond this general, science-specific structure of the creative process, there are also science-specific tools that can support and enhance its realization. For example, human brains naturally adopt the intentional stance, where we make assessments and predictions based on the notion that objects behave according to intentions13. Science educators, however, often discourage students from using this powerful source of intuition, as it may lead to imprecise formulations. Here — as also elsewhere — science education appears to be geared toward suppressing rather than enhancing the creative capacities of students. This situation needs to change. Human creativity thrives on the use of anthropomorphisms and other metaphors, and students need to learn how to exploit this skill while maintaining the ability to translate any imprecise language into precise day-science language14.
The most powerful tool for creative science might be improvisational scientific discussions, both with close colleagues and with experts in related fields. Scientists-in-training should learn how to use them productively to explore contradictions, riddles and new directions, and how to not dismiss new ideas out of hand15,16. Another important strategy to boost scientific creativity is to import concepts and tools from other fields3, such as in the case of biologists who studied interactions among yeast cells by importing game theory concepts from economics17. Conversely, we can export tools and ideas from our field to others, as did quantum physicists who initiated the development of quantum computers18.
Through a scientific creativity course, students can learn that when getting stuck in the search for a solution, progress can be made by framing the project as a different kind of puzzle19. For example, they might have approached their project as a jigsaw-like puzzle — simply searching for the right connections between the pieces — when in fact the solution was unreachable without dropping an implicit assumption about where it should be found. Although it often seems that the role of scientists is to provide answers, we must teach how to refocus existing questions and to ask new ones: inventing the right question can advance science more than answering an existing one20. Moreover, discoveries often arise from exploratory data analysis, which students should learn to pursue in a hypothesis-free manner alongside hypothesis-driven approaches — thereby sustaining the eternal conversation between data and hypotheses4. The creativity toolbox of seasoned practitioners of the scientific method includes these and other thinking tools, and integrating the personal experiences of individual researchers could make night science courses more accessible to students. But many mentors may not be consciously aware of their creative tools, and hence cannot explicitly teach them to their mentees.
The benefits of explicitly teaching the creative side of the scientific method would extend beyond the advancement of science to foster a more supportive culture. Learning to appreciate the tortuousness and unpredictability of the scientific process will promote the well-being of graduate students, for whom the process often results in a sense of failure and meaninglessness21. This learning will equip scientists-in-training with tools to apply when they are stuck with failures or contradictions, and they would learn how open and creative discussions could counteract feelings of anxiety and insufficiency. From our experience in the past few years, there is a thirst among graduate students for this specific kind of education, which should be given the same importance as their compulsory courses (such as ethics and statistics) in graduate programs22. A renewed emphasis on creativity in the sciences would also help to reduce misconceptions among the public about the scientific process, encouraging increased numbers of creative young people to pursue a career in science.
A major change to the system of scientific research, aimed at increasing the creativity and disruptiveness of science projects, undoubtedly requires a multifaceted response. Training graduate students in the creative side of the scientific process can form an important piece of this response. The first effects of this development will materialize almost immediately and its full rewards will be reaped over time, as the scientists-in-training become principal investigators themselves.
- Park, M., Leahey, E. & Funk, R. J. Nature 613, 138–144 (2023).PDF opens in a new tabArticle CAS PubMed Google Scholar
- Bloom, N., Jones, C. I., Van Reenen, J. & Webb, M. Am. Econ. Rev. 110, 1104–1144 (2020).Article Google Scholar
- Yanai, I. & Lercher, M. Genome Biol. 21, 67 (2020).PDF opens in a new tabArticle PubMed PubMed Central Google Scholar
- Yanai, I. & Lercher, M. Genome Biol. 21, 231 (2020).PDF opens in a new tabArticle PubMed PubMed Central Google Scholar
- Yanai, I. & Lercher, M. A course on the creative scientific process. Night Science https://night-science.org/a-course-on-the-creative-scientific-process/ (accessed 14 March 2023).
- Night Science. BMC https://www.biomedcentral.com/collections/night-science (accessed 14 March 2021).
- Yanai, I. & Lercher, M. Night Science https://nightscience.buzzsprout.com/ (2023).
- Yanai, I. & Lercher, M. Genome Biol. 20, 179 (2019).PDF opens in a new tabArticle PubMed PubMed Central Google Scholar
- Jacob, F. The Statue Within: An Autobiography (CSHL Press, 1995).
- Strevens, M. The Knowledge Machine: How Irrationality Created Modern Science (Liveright, 2020).
- Hunter, S. T., Bedell, K. E. & Mumford, M. D. Creativity Res. J. 19, 69–90 (2007).Article Google Scholar
- DeHaan, R. L. CBE Life Sci. Educ. 8, 172–181 (2009).Article PubMed PubMed Central Google Scholar
- Dennett, D. C. The Intentional Stance (MIT Press, 1987).
- Yanai, I. & Lercher, M. Genome Biol. 21, 147 (2020).PDF opens in a new tabArticle PubMed PubMed Central Google Scholar
- Alon, U. Why science demands a leap into the unknown. ted.com https://www.ted.com/talks/uri_alon_why_science_demands_a_leap_into_the_unknown (2014).
- Yanai, I. & Lercher, M. Genome Biol. 23, 4 (2022).PDF opens in a new tabArticle PubMed PubMed Central Google Scholar
- Gore, J., Youk, H. & van Oudenaarden, A. Nature 459, 253–256 (2009).PDF opens in a new tabArticle CAS PubMed PubMed Central Google Scholar
- Benioff, P. J. Stat. Phys. 22, 563–591 (1980).Article Google Scholar
- Yanai, I. & Lercher, M. Genome Biol. 23, 179 (2022).PDF opens in a new tabArticle PubMed PubMed Central Google Scholar
- Yanai, I. & Lercher, M. Genome Biol. 20, 289 (2019).PDF opens in a new tabArticle PubMed PubMed Central Google Scholar
- Bolotnyy, V., Basilico, M. & Barreira, P. J. Econ. Lit. 60, 1188–1222 (2022).Article Google Scholar
- Ness, R. B. Acad. Med. 86, 1201–1203 (2011).Article PubMed Google Scholar