The prestige journal Nature published a paper yesterday called “Papers and patents are becoming less disruptive over time”, which was accompanied by the news article “‘Disruptive’ science has declined–and no one knows why.” This is the latest in a small but growing body of evidence that science is slowing down (1-3). These findings come from an emerging field called the ‘science of science’, which is in essence the act of turning science on itself. However, while the motivation is simple enough, headlines like this one are puzzling, boarding on bizarre. If you ask a scientist about these results, they will tell you exactly why this is happening. Randy Bruno is a professor of neuroscience at the University of Oxford, and retweeted the paper noting that many of the underlying incentives for incremental, rather than risky or groundbreaking, work are well known.
Head to the closest pub or coffee shop to a major research center and you’ll hear a litany of reasons why scientific innovation and creativity are being hampered. The typical targets? Funding agencies, journals, and academic administration. First on the list is the largest funding agency in the United States, the NIH, otherwise known as ‘Not Invented Here’. Beyond sour grapes complaints, there is evidence that the funding body has become more conservative over time and that high-risk projects are less likely to be funded (4).
My own experience with the NIH represents a common complaint against the agency, which is that they determine funding based on the amount of preliminary results. During my PhD I submitted an F31 fellowship that would support my salary during graduate school. On the first round of submission it was scored in the 38th percentile, which is a distant 15-20 points from the funding cutoff. When I submitted my application again a few months later it scored in the 3rd percentile, essentially guaranteeing I would be funded. The only difference between the two versions? The amount of data. Not one idea had changed. The only difference was, I had already done most of the work. It had become a safe bet–all without the NIH ever giving the project a dime.
While frustrating and real, this problem is not as bad as it seems. Depending on where the grant funds are coming from, researchers have a fair amount of discretion with how they use grant funding. I abandoned that project that I applied for F31 funding for, without consequences. Research grants commonly have reporting requirements and conditions for renewal, but as long as the grant results in some relevant publications, no one looks too closely. You need the preliminary data to get the grant, but once you have it you can mostly follow the science wherever it leads.
Next on the list are scientific journals, and here the impact is hard to overstate. Publishing is the bottleneck and arbiter of the system. Having the right papers in the right journals determines a scientist’s funding and career trajectory. One of the loudest critics of the publishing industry is Michael Eisen, a professor of genetics and development at UC Berkeley as well as the editor-in-chief of the journal eLife. Recently, eLife made waves of its own by announcing they would no longer accept or reject papers after peer review. To Nature’s headline that ‘no one knows why’ science is becoming less disruptive, he pointed out the deep irony of this headline coming from Nature, who he views as one of the major drivers of our current research climate.
Journals like Nature, Science, and Cell (known collectively as CNS), hold an extreme amount of power over the research that gets done. To publish in these journals, researchers must create publications that are ‘high impact’, meaning they will likely be cited by other papers in the future (hopefully before the next grant is due). At the publishing stage, researchers will spend 1-3 years after the work is done doing more experiments and writing rebuttal after rebuttal to convince the editor that no really, you should publish this paper here. The deeper issue, however, is that this imperative has infiltrated every step of the research process. Scientists abandon ideas that don’t immediately seem flashy, favor the latest techniques despite their cost and unproven capabilities, and tack on superfluous experiments that follow a current trend. In the life sciences the tendency is to also artificially link the work to a disease area, which provides an automatic boost.
Most of all, we are taught to focus on turning our work into a ‘story’ that is easy to understand and communicate to others. This is not entirely bad. Itai Yanai, a professor of biochemistry and molecular biology and founding director of the Institute for Computational Medicine at NYU, makes the case for why the motivation behind ‘story’ is important. Papers need to be organized into coherent ideas, not just be a dump of data or equations, in order to effectively communicate results to the world. Doing that effectively is part of the ‘philosophy’ of science–how pieces of information come together to become knowledge. However the march towards ‘story’ has become a mandate to tailor your work towards what journals want to see, from project conception to finished manuscript.
There will always be a space between a coherent idea and the truth, as we are fundamentally limited in our ability to perceive the natural world. Papers are always just a representation of something bigger and more real, like the painting by René Magritte ‘The Treachery of Images’. But science today has warped into a much more harmful representation: the space between individual pieces of the data and the ‘story’. Scientists, generally, work very hard for relatively little money because they genuinely want to make discoveries. Everyone wants to write the classic paper that is still referenced in 100 years. But to advance your career, you need an easily digestible story that will be immediately popular–and you should seek, interpret, and present your data accordingly. This is a constant cycle of short-term thinking that does not tolerate slow, sometimes boring, sometimes weird work that lies outside the mainstream. That also means it does not tolerate the work that has the potential to become disruptive.
"La Trahison des Images" 1928-9 by René Magritte. Owned and exhibited at LACMA
Nature, we do know why science has become less disruptive, and so do you. Safe bets are funded, and the pressure to publish in journals like yourself has squeezed research into a one-size-fits all pipeline. Universities feed off the indirect costs that come from grant funding, closing the incentive loop. This does not produce good scientific outcomes long-term, as we now see. It also pushes out many researchers, who are frustrated and fed up with serving a system that feels like it cares about all the wrong things. I’m glad that people from outside of the life and physical sciences are turning their attention to the academic science sector. This kind of data motivates change from a stagnant system. But, in truth, so much of the initial ideas for why are relatively learnable. All you need to do is show up to the nearest academic pub and you’ll find person after person who will tell you exactly why we’re less disruptive than we used to be. The science of science would do well to listen.
Pammolli, F., Magazzini, L., & Riccaboni, M. (2011). The productivity crisis in pharmaceutical R&D. Nature reviews Drug discovery, 10(6), 428-438.
Bloom, N., Jones, C. I., Van Reenen, J., & Webb, M. (2020). Are ideas getting harder to find?. American Economic Review, 110(4), 1104-44.
Chu, J. S., & Evans, J. A. (2021). Slowed canonical progress in large fields of science. Proceedings of the National Academy of Sciences, 118(41), e2021636118.
Packalen, M., & Bhattacharya, J. (2020). NIH funding and the pursuit of edge science. Proceedings of the National Academy of Sciences, 117(22), 12011-12016.