On serendipity in science: discovery at the intersection of chance and wisdom

Abstract

‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of serendipity in science as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities.

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Fig. 1

Notes

  1. 1.

    Walpole refers in this passage to the Princes of Serendip, characters in a fairy tale who inspired him to label this phenomenon ‘serendipity’ because of how they make valuable use of accidental observations.

  2. 2.

    Of course, in philosophical discussion about the logic or rationality of scientific discovery, there is a deep and complicated debate concerning abduction (see work by Peirce, Paavola, Hanson, Hintikka, for example). How well abduction works as a description of the reasoning involved in some cases of serendipity (see the following paragraphs) is a topic I pursue elsewhere, and is outside of the scope of this paper.

  3. 3.

    This is also frequently called synchronicity in the serendipity literature, following Jung: “simultaneous occurrence of two meaningfully but not causally connected events” (as quoted in Liestman 1992, p. 527). Liestman’s (1992) use of synchronicity as one category of serendipity in library research is picked up by several others, from fields such as computer–human interaction (Kefalidou and Sharples 2016), education (Nutefall and Ryder 2010) and information studies (Foster and Ellis 2014). Synchronicity is also appealed to by organizational and management theorists (see Cunha 2005 for further references). However, I follow Lawley and Tompkins (2008), who draw a distinction between synchronicity and serendipity, because the former is recognized immediately whereas the latter is not (see Sect. 2).

  4. 4.

    There are many chance aspects of even this observation, including the perfect temperature fluctuations in London at the right time, an open door to a stairwell, and Fleming’s vacation (Diggins 1999, p. 87). Chance marked the path to penicillin’s mass-production as well—to name one instance, lab assistant Mary Hunt was at the local market when she picked up a moldy cantaloupe, which led to the discovery of a better medium for penicillin’s production, despite the hundreds of samples sent from afar to the lab for just that purpose. The insightful assistant in this case was, however, rewarded with a nickname—‘Moldy Mary’—rather than a Nobel Prize.

  5. 5.

    A possible exception is Kohn’s (1989) book, Fortune and Failure: Missed Opportunities and Chance Discoveries in Science. However, as with the example given by Barber and Fox, the ‘forgotten’ discoveries in this book are only seen as such in light of the discoveries that were (later) actually made.

  6. 6.

    Given the quotation from Nickles above, one might extend this retrospectivity to many discovery processes, but since it would not extend to all processes categorized as discovery processes (since some are indeed intentional, for example, and therefore prospective), ‘serendipity’ remains a particular classification within that broader category (ie: a kind of discovery process that is recognized retrospectively).

  7. 7.

    Of course, in some cases this timeline is collapsed, such as when the value of the discovery is clear at the time of observation. One example might be when a collector of fine garden gnomes happens by chance to visit a friend whose neighbor is holding a garage sale and selling a gnome whose value the collector is able to identify immediately. But more often, including in the examples Walpole himself gives and (I would argue) almost always in the case of scientific discovery, multiple steps are required to reveal the true value of the unexpected finding. And still, the gnome collector could not have known her visit to the friend would be serendipitous beforehand (or it wouldn’t have been, by definition).

  8. 8.

    Cunha (2005) and Lawley and Tompkins (2008) developed the first process models through an analysis of case studies and the literature. The later articles cited here refer to studies that confirmed and refined that model via empirical research (i.e.: interviews).

  9. 9.

    See Anjum and Mumford (2017) for an example of an account of emergent properties as those properties that do not belong to the parts but rather arise from an interaction between parts as novel properties of the whole.

  10. 10.

    Nassim Taleb provides a similar approach to what he calls Black Swans—catastrophic events that came by surprise (2007). Taleb highlights the fact that although in retrospect we are often able to explain how Black Swan events occurred, cognitive biases prevent us from predicting their occurrence beforehand. However, even if we were perfectly aware of our cognitive biases, Black Swans would still occur.

  11. 11.

    Most notably, Fleming himself, who humbly declared during his Nobel Prize Award speech that, “My only merit is that I did not neglect the observation and that I pursued the subject as a bacteriologist” (Fleming 1945).

  12. 12.

    I am far from alone in pointing out, for instance, that others had made similar observations but had lacked the timeliness and social connections that Fleming had. A fairly well-known example is the French graduate student Ernest Duchesne, whose dissertation reporting on the therapeutic effects of another Penicillium mold was submitted in 1897. Duchesne’s work remained unknown and he died a few years later, however, and so his preliminary efforts were not taken up to be part of the discovery process that ultimately led to penicillin (see Copeland 2015, pp. 63ff for this and other examples).

  13. 13.

    Aspects of these first two questions are often discussed under the problem of the division of cognitive labour (see Kitcher 1990; Weisburg and Muldoon 2009, for examples).

  14. 14.

    I would like to thank an anonymous reviewer for drawing my attention to the relevance of this discussion.

  15. 15.

    As Strevens (2017) points out, not only data is of value when it comes to sharing scientific knowledge. In keeping with the variations of serendipity I have described above, all sorts of information might have unexpected value, enabling a discovery by making it timely or by creating a social connection between scientists that leads to the exchange of further information, for example.

  16. 16.

    A further factor in the discussion over Franklin’s contribution to this discovery concerns whether Watson and Crick illegitimately gained access to Franklin’s data. Michelle Gibbons offers insight into the relevance of that discussion for determining Franklin’s role and offers a complementary approach to the discovery in her article, “Reassessing Discovery” (Gibbons 2012).

  17. 17.

    One can assume there will always be unexpected observations or events, so long as scientists fall short of omniscience.

  18. 18.

    Howard Gest points to a similar factor in his recounting of serendipity in the isolation of the vitamin C molecule—the fact that one group of scientists had a much faster and less costly test available to them allowed for their belated, yet successful involvement in that discovery process (Gest 1997, p. 23).

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Acknowledgements

I would like to extend thanks to the CauseHealth team, my dissertation committee, the Dalhousie Philosophy Department colloquium, and various conference audiences for their constructive criticism and insightful questions. Two anonymous reviewers provided thoughtful advice on how to improve upon previous versions. Funding was provided by The Research Council of Norway (FRIPRO). The Research Council of Norway (NFR, FRIPRO scheme).

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Copeland, S. On serendipity in science: discovery at the intersection of chance and wisdom. Synthese 196, 2385–2406 (2019). https://doi.org/10.1007/s11229-017-1544-3

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Keywords

  • Serendipity
  • Scientific discovery
  • Social-epistemology of science
  • Chance