03/04/2023 - Journal Club

Papers and patents are becoming less disruptive over time

by Marc Pauper and Ayesha Feroz

The fields of science and technology have been the engines of progress for many years, driving innovation and shaping the world we live in. Contributing to this scientific knowledge and progress is one of the main aspirations most of us researchers have. However, there is a growing number of studies suggesting that scientific progress is slowing in several fields (13). In today’s journal club, we present the work of Ph.D. candidate Michael Park, prof. dr. Erin Leahy and prof. dr. Russel J. Funk, titled “Papers and patents are becoming less disruptive over time” published in Nature last month, where they explore this phenomenon by conducting a large-scale analysis of the innovative activity in science and technology (4). This study is based on 25 million papers from the years 1945-2010 from the Web of Science and 3.9 million patents of the United States Patent and Trademark Office from the years 1976-2010, to try to understand both the extent of the slowdown in innovation and the reasons behind it.

To begin, the authors based their analysis on the distinction of two types of breakthroughs: consolidating contributions and disruptive contributions. The former are works that improve and contribute to further establishing existing knowledge, while the latter challenge current understanding making it obsolete and therefore driving science and technology towards new frontiers. To quantify this characteristic, the authors relied on a metric called the CD index (5), which is based on the number of citations a paper or patent receives and how these citations relate to previous work in the field. As Park et al. best put it: “[…] if a paper or patent is disruptive, the subsequent work that cites it is less likely to also cite its predecessors […] If a paper or patent is consolidating, subsequent work that cites it is also more likely to cite its predecessors”. Figure 1 illustrates the concept of CD index and shows some examples.

Figure 1: This figure shows a schematic visualization of the CD index. a, CD index value of three Nobel Prize-winning papers and three notable patents in our sample, measured as of five years post-publication (indicated by CD5). b, Distribution of CD5 for papers from WoS (n = 24,659,076) between 1945 and 2010 and patents from Patents View (n = 3,912,353) between 1976 and 2010, where a single dot represents a paper or patent. The vertical (up–down) dimension of each ‘strip’ corresponds to values of the CD index (with axis values shown in orange on the left). The horizontal (left–right) dimension of each strip helps to minimize overlapping points. Darker areas on each strip plot indicate denser regions of the distribution (that is, more commonly observed CD5 values). c, Three hypothetical citation networks, where the CD index is at the maximally disruptive value (CDt = 1), midpoint value (CDt = 0), and maximally consolidating value (CDt = −1). The panel also provides the equation for the CD index and an illustrative calculation.

By measuring the CD index of each paper and patent at 5 years after publication, the authors were able to determine that there is a massive decline in disruptiveness in science and technology across all major fields in the last decades (decline 91.9-100% for papers, 78.7-91.5% for patents) (figure 2). The authors found the same trend also using other indicators, namely the linguistic composition of published titles and abstracts. For example, the type-token ratio (unique words to total words) of paper and patent titles has declined significantly, especially before 1970 for papers and 1990 for patents, and a similar decline was observed in the combinatorial novelty of the words used. Finally, there is a decrease in the novelty of the combinations of previous work cited by papers and patents.

Fig 2. Decline in CD5 over time, separately for papers (a, n = 24,659,076) and patents (b, n = 3,912,353)

The authors found that the decline in disruptive activity was not due to a decrease in the quality of science and technology or an artifact of the CD index itself. They observed similar patterns of decline in disruptiveness when they computed the CD index using other data sources, such as JSTOR and PubMed. They also found that the decline was not due to changing publication or citation practices by conducting additional analyses, such as regression models and Monte Carlo simulations. Park et al. also considered the relationship between the growth of knowledge and the decline in disruptiveness. While they found conflicting results, with a positive effect of the growth of knowledge on disruptiveness for papers and a negative effect for patents, they observed a decline in the use of previous knowledge among scientists and inventors. This suggests that scientists and inventors are increasingly focusing on narrower slices of previous work, which could be limiting the potential for disruptive discoveries and inventions.
In conclusion, this study provides evidence of a decline in disruptive activity in the fields of science and technology and suggests that this decline may be related to a decline in the use of previous knowledge among scientists and inventors. This highlights the importance of fostering an environment in which scientists and inventors can engage with a diverse range of knowledge, which is crucial for driving disruptive discoveries and inventions.

References

  1. B. F. Jones, The Burden of Knowledge and the “Death of the Renaissance Man”: Is Innovation Getting Harder? Rev. Econ. Stud. 76, 283–317 (2009).
  2. N. Bloom, C. I. Jones, J. Van Reenen, M. Webb, Are Ideas Getting Harder to Find? Am. Econ. Rev. 110, 1104–1144 (2020).
  3. J. S. G. Chu, J. A. Evans, Slowed canonical progress in large fields of science. Proc. Natl. Acad. Sci. 118, e2021636118 (2021).
  4. M. Park, E. Leahey, R. J. Funk, Papers and patents are becoming less disruptive over time. Nature. 613, 138–144 (2023).
  5. R. J. Funk, J. Owen-Smith, A Dynamic Network Measure of Technological Change. Manag. Sci. 63, 791–817 (2017).

Q&A with Michael Park

Michael Park, one of the authors of the publication, kindly agreed to answer some questions we had:

Ayesha and Marc: Your work suggests that the observed decline in disruptive scientific findings is possibly related to the “publish or perish” culture. A deviation from this would necessitate deeper reforms in policies and is unlikely to occur in the short term. What would be your advice, to us as a network of Ph.D. students, to mitigate the effect of the “publish or perish” culture and increase our chance to produce truly innovative findings?

Michael: I would just point out that this is beyond the scope of our study and the scientific community would benefit from further research on how researchers can better navigate the potential pitfalls of the «publish or perish» culture. Nevertheless, I am happy to share some of my casual thoughts on this. Although it can be difficult, I think trying to not be too limited in the breadth of your research pursuit is important. For example, staying informed about the latest research in not only your own specific field but adjacent fields as well could be helpful. Actively seeking out collaborations with scientists from other disciplines may also be enriching. Although there may be many reasons why disruption is decreasing across time, our paper does suggest that a narrow research focus limited to specific fields is closely linked to nondisruptive research. 

Ayesha and Marc: We are currently seeing major breakthroughs in the field of artificial intelligence and conversational models. Do you think such AI tools can play a catalyzing role to help scientists digest and combine the increasing stock of knowledge? A scaffold, of sorts, that would help us climb on the shoulders of ever taller giants?

Michael: Again, the question is outside of the scope of the paper as well as my main research area since I don’t specialize in AI research. Nevertheless, I am happy to share my non-expert opinion if you would like. I think AI may help make certain parts of the research process more efficient, such as literature review, data analysis, and writing. However, I think the idea generation aspect of research, which is most influential in determining the extent to which a piece of work is disruptive, will largely remain a human task. Therefore, unless there is some AI technology that is capable of producing disruptive new ideas (there may well be as you point out), I personally don’t think AI adoption in research and education will lead to an increase in disruptive discoveries and inventions.

Ayesha and Marc: A more philosophical question: Some support the idea that because humans are biological organisms, they have a specific scope and limits, and that includes their cognitive capacities (for example “What Kinds of Creatures are We?” by Noam Chomsky). What is your opinion on this? Is scientific and technological progress doomed to halt someday? Could the decline in disruptiveness shown in your study be an early indication of this phenomenon?

Michael: I do agree that a human being does have cognitive limitations. This is part of the reason why when researchers are forced to publish many papers quickly, they limit the scope of their specialty, which seems to be linked to the decline in disruptiveness. However, I don’t think the linkage between cognitive limitations and research scope suggests that we are near the «doomed» day yet. Although individual human beings may be limited in their cognitive capacity, science progresses due to the efforts of a community of people. Researchers feed off of the advances but also the limitations of others’ works. So I don’t necessarily think that the cognitive capacities of human beings are detrimental to the creation of disruptive work. In addition, we show in Figure 4 that the number of highly disruptive works is pretty consistent across time. This likely suggests that we are not «running out» of disruptive things to discover.

Below is Figure 4 of the article mentioned above.

This figure shows the number of disruptive papers (a, n = 5,030,179) and patents (b, n = 1,476,004) across four different ranges of CD5 (papers and patents with CD5 values in the range [−1.0, 0) are not represented in the figure). Lines correspond to different levels of disruptiveness as measured by CD5. Despite substantial increases in the number of papers and patents published each year, there is little change in the number of highly disruptive papers and patents, as evidenced by the relatively flat red, green and orange lines. This pattern helps to account for simultaneous observations of both aggregate evidence of slowing innovative activity and seemingly major breakthroughs in many fields of science and technology. The inset plots show the composition of the most disruptive papers and patents (defined as those with CD5 values >0.25) by field over time. The observed stability in the absolute number of highly disruptive papers and patents holds despite considerable churn in the underlying fields of science and technology responsible for producing those works. ‘Life sciences’ denotes the life sciences and biomedicine research area; ‘electrical’ denotes the electrical and electronic technology category; ‘drugs’ denotes the drugs and medical technology category; and ‘computers’ denotes the computers and communications technology category.

Cover Image source: https://ellipse.prbb.org/the-art-of-publishing-a-scientific-article/

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