scribe the unintentional, accidental, and lucky discoveries1 both in lay .... velopment of events by chance in a happy or beneficial wayâ [emphasis added].
The Antinomies of Serendipity How to Cognitively Frame Serendipity for Scientific Discoveries
Abstract During the second half of the last century, the importance of serendipitous events in scientific frameworks has been progressively recognized, fueling hard debates about their role, nature, and structure in philosophy and sociology of science. Alas, while discussing the relevance of the topic for the comprehension of the nature of scientific discovery, the philosophical literature has hardly paid attention to the cognitive significance of serendipity, accepting rather than examining some of its most specific features, such as its game-changing effect, the unexpectedness of its occurrence, and its affinity with the concept of “luck”. Thus, in this paper we aim at analyzing these characteristics in the light of their cognitive implications in the recognition, performance, and possible stimulation of serendipitous events in relation to scientific discoveries. Key words: Serendipity; Scientific Discovery; Epistemic Luck; Ignorance; Anticipation; Abduction.
Introduction: The Three Pillars of Serendipity in Science Serendipity is a topic of growing fame in the panorama of sociology and philosophy of science. Despite its humble origins as a term ideated by Horace Walpole (1789) in reference to “a silly fairy tale” , it has been used in the past fifty years to describe the unintentional, accidental, and lucky discoveries1 both in lay environments and in the scientific framework. In the latter category some game-changing events for the history of science stand out as unquestionable instantiations of serendipity: Fleming’s discovery of penicillin (cited by Slowiczek and Peters (2007); Kakko and Inkinen (2009); McCay-Peet and Toms (2015)), Antoine Henri Becquerel’s finding of X-rays (cited by Cannon (1940); Allen et al. (2013); Rosenman (1988)), Wat1
On the significance of the term “lucky” and the concept of luck in epistemic attainment we will further comment in footnote 2 and in the first section of the article.
1
2
son and Crick’s reflection on the alpha-helix structure of DNA (cited by Darbellay et al. (2014); Campanario (1996); Copeland (2017)), and the list grows longer as the historiographical narrations (and the contemporary scientific reports) become more detailed. Indeed, the fortune of the term serendipity is connected to the recent acknowledgement of the role of chance in scientific processes (Cannon, 1940; Austin, 2003; Kipnis, 2005; Catellin, 2014) as well as the importance of a skillful perspective that scientists need to enact in order to exploit those lucky events (Allen et al., 2013; Copeland, 2017). Considering this increasing attention to the role of both intentional/explicit and unintentional/accidental factors that affect the course of scientific endeavors, finding a defining formula for serendipity has acquired relevance in the context of philosophy of science. Therefore, numerous scholars have tried to draw a clarifying description for the occurrences of serendipity in science. For example, the definition provided by Walpole (1789) (as quoted by Merton and Barber (2010, p. 2)) – “discoveries [made] by accidents and sagacity, of things [the observers] were not in quest of” – has been used to describe serendipity as an event or a moment (Baumeister et al., 2010), as well as a process (McCay-Peet and Wells, 2017), and “a category used to describe discoveries in science that occur at the intersection of chance and wisdom [. . . ] an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward” (Copeland, 2017, p. 1). Highlighting the role of social interaction and environmental triggers that spur the emergence of serendipity in science, some authors defined it “as an unexpected experience prompted by an individual’s valuable interaction with ideas, information, objects, or phenomena” (McCay-Peet and Toms, 2015, p. 392). Others gave a pluralistic definition of the concept, speaking about different types of serendipity (Kantorovich, 2016), borderline occurrences (such as the idea of pseudoserendipity ideated by Roberts (1989), which we will further comment in footnote 3), or decomposing the concept in relevant parts (e. g. Anciaux’s list: “the gift, the discovery, the accident, the sagacity, the things, and the non-search” (Brown, 1994)). All of these definitions have been serving the purpose of focusing on one aspect of serendipitous occurrences to comprehend, analyze, and maybe stimulate their emergence in scientific contexts. Nevertheless, defining serendipity is not the only solution to provide clarity for its occurrences in science. We believe that by understanding the cognitive features that characterize serendipity, which transcend and encompass the particular definitions provided above, we can further clarify how it is enacted in the context of scientific discovery and resolve some paradoxical issues that regard it. The cognitive features can be summed up in three distinct items: 1. Serendipity is generally defined as a positive experience and so it has been often connected to the topic of luck.2 2
The topic of epistemic luck is a very controversial one in the epistemological literature. The problems emerge when it is debated if knowledge can be attained by luck (Pritchard, 2004; Morris, 2012; Ranalli, 2013) and, if the thesis that it can happen is defended, whether it is possible to strictly separate lucky-gained knowledge from knowledge of any other kinds (Rohwer, 2014). In
The Antinomies of Serendipity
3
2. Serendipity is unexpected; its accidental nature is embedded in this feature. It can refer both to an unexpected outcome – which the scientists were not looking for – or to the emergence of an unexpected way to find something that the scientists were in search of.3 3. Serendipity is game-changing in science. It does not only bring a new perspective on the scientific research enacted by scientists who experience it, but it revolutionizes their findings, by altering their view of what is relevant and what is not. By comparing the various definitions and debates about the concept of serendipity, it is apparent that discussing its importance for scientific endeavors implies dwelling with all these traits. At the same time, all of these features, which are mostly accepted rather than discussed by the relevant literature, unfold contradictory corollaries if connected to actual instantiations of serendipity in science. For example, the first trait, which highlights the connection between serendipity and luck, poses a problem of demarcation: when could we consider a scientific discovery the result of a serendipitous event rather than luck, or “dumb luck”, even? Moreover, despite the fact that serendipity is unexpected, the preparation of the scientist who experiences it is mostly deemed as necessary to exploit this chance (McBirnie, 2008; McCay-Peet and Toms, 2015; Copeland, 2017). How could we connect preparation with an unexpected experience? At the same time, the game-changing feature is seen just retroactively (Copeland, 2015; Campanario, 1996; Baumeister et al., 2010) deeming the serendipitous moment as either the beginning of the change of perspective or its conclusive outcome. Could we ask when and how serendipity changes the rules of the game for the interested scientists? These questions and issues do not refer to a specific definition of serendipity or of a particular instantiation of it, but are nested into the different descriptions that various authors used in order to address it. Thus, in this article we hope to bring clarity on the description of serendipity in science discussing its three main features, in the light of their cognitive implication in the recognition, performance, and possible stimulation of serendipitous events in relation to scientific discoveries. In the first section we will distinguish the concepts of luck and serendipity by considering the recognition and exploitation of ignorance that the scientists need to perform in cases of serendipitous discoveries and that do not occur in cases of lucky epistemic this article, even if we will discuss the concept of luck in epistemic gain, we will not actually defend the position that knowledge can be obtained by luck because we will explicitly distinguish luck (or even epistemic luck) from serendipity, even if some authors (Pritchard, 2004) seem to reduce the latter concept to the former. As we will argue in the first section, luck has a role in serendipity, but the epistemic gain is attained by more than just dumb luck and rather as a conjunction of a lucky occurrence and an active contribution of the agent who recognizes and exploits her own ignorance. 3 By referring to the two situations, Roberts (1989) distinguishes between “pure serendipity” – when the outcome is not looked for – and a “pseudoserendipity” – when the outcome is looked for but the discovery was accidental. We agree with Copeland (2017) in saying that this distinction is fairly useless to understand the role of serendipity in scientific processes. More than often, finding a method to reach a particular outcome is the goal of the research, as well as finding a particular outcome that emerges at the end of a process of testing. Either way, unexpectedness defines the occurrence of a serendipitous factor in the process of discovery.
4
gain. In the second section we will discuss how the unexpected event of serendipity can be thought as surprising but nevertheless anticipated (Rosen, 1985) by the prepared scientist. Finally, in the third section, we will discuss the game-changing property of serendipity by analyzing its occurrence as matching the emergence of the trans-paradigmatic abduction (Hendricks and Faye, 1999).
1 Doubt and Investigative Ignorance: Explaining the Lucky Side of Serendipity The Oxford English Dictionary describes serendipity as “the occurrence and development of events by chance in a happy or beneficial way” [emphasis added]. Because of the inherent trait of being an event or a process that drives the agents “by chance” to positive outcomes, serendipity has been often associated with the concept of luck. On this regard, the scholars interested in the development of the understanding of serendipity in science mainly focused on two considerations. The first one regards the role that chance, accident, and even luck have in the progress of science. Some (Cannon, 1940; Merton and Barber, 2010; Kipnis, 2005) highlighted that it is important for the development of a honest sociology of science to emphasize the fallible nature of the theoretical and pragmatical organization of experiments and tests. Serendipity, in this matter, is used to call attention to how the lack of control scientists have on their practice may have positive outcomes in particular circumstances. In a way, it is used both to address the often unrecognized part that chance plays in scientific investigations – derived from the unseen errors of scientists, their practical mistakes, their random quests – and to lay an apologetic vest on them, deeming the scientific endeavor open to unsought possibilities for good reasons. The second consideration regards how the connection between serendipity and luck does not imply the reduction of the former concept to the latter, which describes fortunate events that happen without the active contribution of the interested individual. Even the description of the epistemic luck given by Pritchard (2004) (which is composed by the union of the descriptions L1 and L2) does not imply any practical part played by the agent in order to exploit the unexpected chance: L1 If an event is lucky, then it is an event that occurs in the actual world but which does not occur in most of the nearest possible worlds to the actual world (worlds which most resemble the actual world) (p. 197). L2 If an event is lucky, then it is an event that is significant to the agent concerned (or would be significant, were the agent to be availed of the relevant facts) (p. 199).
The agent, to be subject to epistemic luck, needs only to give relevance to a particular event with an effect on her knowledge. Serendipity, in this sense, is connected to the concept of luck, but requests more from the agent in order to be enacted. Indeed, the positive outcomes of serendipity are considered as the result of not only the lucky events involved, but also the “right mind” of the scientists who were able
The Antinomies of Serendipity
5
to exploit them. To comment on this, numerous authors (Rosenman, 1988; Darbellay et al., 2014; McCay-Peet and Wells, 2017) who dealt with the complexity of serendipity quoted the famous words of Pasteur “Chance favors only the prepared mind” (Pasteur, 1937, p. 131) and “Having the capacity to be surprised when it matters is the beginning of the mind’s journey of discovery” (Pasteur, 1922, p. 370). Words such as “sagacity” and “wisdom” have been used to comprehend what a scientist needs to master in order to perform and recognize a serendipitous act, moment or event (Copeland, 2017), while other authors (Foster and Ford, 2003; McCay-Peet and Toms, 2015) have instead tried (sometimes in vain) to make a list of characteristic traits that need to be acquired to elicit those occurrences. Thus, notwithstanding the general agreement regarding the separation between luck and serendipity, these phrases do not highlight a particular skill of the involved scientist’s preparation, even if they imply that, in order to exploit serendipity in science, one needs to do more than to be “in the right place at the right time”. In few words, they suggest that a scientist who finds herself serendipitously discovering something, should have both the disciplinary specialization to recognize the finding and the open-mindedness to acknowledge that event as a serendipitous occurrence. Thus, how could we consider a more detailed description of these preparatory states that can explain some situations as cases of serendipity, and not merely dumb luck? A way to address this question from both a cognitive and an epistemological point of view is to comprehend serendipity and luck as events that emerge from ignorant states. As (Brown, 2010, p. 1) pointed out, serendipity would be pointless if we could ask Google, “Please tell me what I need to know that I don’t know I need to know yet.” Still, the kind of ignorance that is comprehended in Brown’s description is too vague to depict the one that is challenged by a serendipitous event: serendipity not only acts at the intersection of what we do not know but we need to know, but also of what we are able of understanding given our background knowledge and what we do not know yet. For example, as reported by (Copeland, 2016), Fleming was not the only, nor the first one, to observe the antibacterial properties of penicillin: For one, several cases have been raised against the priority of Fleming’s observation of antibacterial properties, in general and specifically in regard to P. notatum itself. He was not the only person to observe these properties. In his Nobel Prize speech, for instance, Fleming remarked that the “inhibition of one microbe by another was commonplace” – bacteriologists of his generation were both taught about such inhibitions and observed them often in practice. As well, to give just one example of an alternate history, Fleming himself once noted that his contemporary and ‘good friend’ Andr´e Gratia “but for circumstance [. . . ] might well have been the discoverer of Penicillin” (de Scoville et al). Gratia’s mistake was in not preserving and distributing his own sample of the mould he had observed. (Copeland, 2016, p. 2)
Luck, as a fortunate event that does not require the active role of the agent to occur, could not be the reason why Fleming, instead of others with the same preparation, made the discovery of penicillin. While luck implies the fact that the agent is merely in a state of ignorance regarding what could occur in particular circumstances, serendipity requires from the agent that she recognizes and exploits that state of ignorance to come up with new and more satisfying information. Thus, how
6
and why Fleming used and exploited his observations is not connected solely to his disciplinary preparation but to the active questioning and doubting of its adequacy. Fleming actively put himself in a situation of what Haas and Vogt (2015, p. 20) call “investigative ignorance”, which occurs when “inquiring minds are committed to assessing with significant and at times seemingly excessive effort whether they are in a position to make claims about the world. They assign probabilities to assumptions, qualify views as preliminary, formulate hypotheses, and so on [. . . ].” This particular type of ignorance lets the agent openly doubt whether she can explain the situation she is observing and claim the necessity of more information. In this sense, serendipity, not luck, emerges when “investigative ignorance” is enacted and gives rise to the state of doubt, in Peircean terms, as an epistemological necessity. To be clear, Peirce describes the state of doubt as an irritating condition for the agent, because it impedes her action (since she does not have sure information to act upon) and forces her to investigate and get more knowledge: Thus, both doubt and belief have positive effects upon us, though very different ones. Belief does not make us act at once, but puts us into such a condition that we shall behave in some certain way, when the occasion arises. Doubt has not the least such active effect, but stimulates us to inquiry until it is destroyed. This reminds us of the irritation of a nerve and the reflex action produced thereby; while for the analogue of belief, in the nervous system, we must look to what are called nervous associations – for example, to that habit of the nerves in consequence of which the smell of a peach will make the mouth water (Peirce, 1998).
This description is particularly interesting because it accurately describes just particular ignorance states: in fact, human agents do not stop in front of every kind of ignorance blocking their way. Arguably, if it were so, many would have made Fleming’s discovery before him. Nevertheless, the enactment of investigative ignorance and of the Peircean state of doubt motivated Fleming to further inquire when others stopped the search, allowing this event to be described as one of the most successful example of serendipity. Thus, while luck presupposes just the presence of a state of ignorance in the mind or the agent, serendipity requires the recognition and exploitation of that state in order to let an epistemic opportunity emerge from it. By distinguishing the concept of serendipity from “mere” or “dumb” luck we also aim at defying the prospect that sees in the connection between serendipity and scientific discovery a way to argue against a “logic” of discovery. One philosopher who expressed this thesis is Cellucci (2017, pp. 136–137) who stated that: Another way of denying that there is a logic of discovery is by appealing to serendipity, which is commonly defined as the faculty of making happy and unexpected discoveries by accident. Some people claim that all discoveries are serendipitous, in this sense. [. . . ] Now, if all discoveries are serendipitous, in the sense of being made by accident, then there is no logic of discovery.
This argument rests on the equivalence drawn by Cellucci and other authors (Kantorovich, 1993; Ippoliti, 2017) between serendipity and a lucky, or “merely accidental”, discovery. But drawing this equivalence means not paying attention to the expertise and preparation of the finders who make the serendipitous discovery
The Antinomies of Serendipity
7
as well as implying that everyone could have made it in the same circumstances. Thus, at the same time, this point of view both reduces serendipity to luck and denies its cognitive and epistemological relevance. Indeed, we need to argue against this view also in order to defy the commonly accepted dichotomy between method and chance, which defines the two terms as exhaustive and mutually exclusive. This is the idea that (Ippoliti, 2017, p. 7) assumes when arguing that: “First, the idea that serendipity can be used as a general model to account for scientific discovery seems untenable for at least two reasons – one quantitative and one qualitative. On one hand, the discoveries made in that way are few, and, at most, they are an epiphenomenon. On the other hand, the very notion of “discovery by chance” does not explain precisely the cases that it employs to support its own view. Fleming, Columbus, or Poincar´e, did not discover “by chance”, but the discovery was made after they used a lot inferences, strategies, and plans – all rational tools. Of course the final product was in a sense unexpected, but it was found after many options had been explored and rejected by the discoverer or others [. . . ], or after several controlled trials [. . . ], or simply the final discovery was not excluded from the very beginning [. . . ].”
With reference to this viewpoint, in this section we aimed instead at recognizing the “accidental” feature of serendipity, while redeeming and redefining its role in the logic of discovery. To this aim, it is worth discussing Gillies’ (2015) particular view on the meaning of serendipity. Commenting the role of serendipity in scientific discoveries, he insists on distinguishing between forms of “serendipitous events” and “accidental discoveries”: the former being a discovery made while looking for something else, and the latter being a discovery made while ”some accidental or chance occurrence plays an important role in the discovery” (Gillies, 2015, p. 526). While we generally agree on the need to discriminate serendipitous discoveries from accidental ones, we still need to clarify that the discriminant for us is the preparation and the expertise of the person who performs the discovery. Gillies, instead, recognizes the discriminant in the aim of the original research: if the person who performs a discovery did not mean to find what she ends up finding, a serendipitous event has occurred; if she wanted to find something and the discovery happens by accident, Gillies describes it as an accidental discovery. To put it more clearly, Gillies reduces the concept of ”pseudoserendipity” coined by Roberts (1989) to mere accidental discoveries. Unfortunately, this reduction, if useful for a sort of metaphysical economy, risks to throw the baby out with the bathwater: we argue that, from an epistemological point of view, it is more interesting and fruitful to evaluate the preparation of the expert who discovers something, with little attention to whether she aimed at discovering it or not from the beginning. Moreover, an impending cognitive and epistemological problem comes out if we discuss how scientists could be “prepared” to enact a state of investigative ignorance instead of betting on good luck in scientific environment. This question, in different form, has a central role in the literature regarding serendipity in scientific endeavors. Many authors do not aim at just providing understanding on how serendipity works, but also on pragmatical ways to spur it in scientific frameworks. As (McBirnie, 2008) states, this issue opens a “paradox of control”: For now, (Van Andel, 1994) serendipity patterns may provide a more neutral description of serendipity without excluding the possibility of a role for control. The sum of these patterns
8 describes serendipity as both passive and active, suggesting that serendipity can involve unexpected results, unexpected changes in direction, and/or the finding of something in unexpected environments or from unexpected sources (McBirnie, 2008, p. 604).
Basically, even if serendipity describes clearly “unexpected” events or processes, one goal of the research is to find a way to elicit serendipitous encounters, to make it happen more and more often, especially in scientific frameworks. More specifically, scholars are looking for a way to elicit accidental events of the right kind to spur the investigation in unpredicted ways. The paradoxical nature of this situation is clear and getting to the bottom of it can be incredibly useful to plan richer research programs and to foster the scientific development in unforeseen directions. Considering the connection established so far between serendipity, investigative ignorance, and doubt, in the next section we will provide a framework to help understand how serendipity can be then described as an unexpected, yet anticipated, event.
2 The Antinomy of Control: Serendipity and the Anticipation of the Unexpected To say that something is both unexpected and anticipated seems quite an oxymoron. But is it? It is necessary to carefully consider, in a philosophical fashion, the meaning of the two words. Something unexpected was, well, not expected, but it is still recognizable, at least to certain cognitive systems. Otherwise, it would be pushed aside by consciousness. This is to say that an unexpected serendipitous event is never a non-sequitur: it sparks an “aha!” reaction, not a “How is that even possible?!”. Fleming’s “Oh!” reaction was when he managed to frame and understand the antibiotic effect of a mold. He did not enter his laboratory to find a moldy culture singing the chorus of Mamma mia!: that would have sparked another kind of reaction. Another way to put it is that some things are reasonably unexpected, some others are wildly unexpected. A famous serendipitous discovery concerns a very basic everyday item, the Post-It note (already commented by (Roberts, 1989; Van Andel, 1994)). 3M’s scientists were trying to achieve an extra-strong glue, and by chance they achieved the exact opposite: a very weak glue with the virtue of holding its (weak) sticking power albeit being detached and reattached over and over. It is clearly a kind of serendipitous discovery, but the chemists and engineers involved were glue-experts, and were able to recognize it. It made sense to them, it did fit the knowledge they had and the projections about their ignorance, so they were able to understand it. Had they stumbled upon something radically different, such as something with no gluing power but an amazing strawberry smell, they would have probably shrugged and thrown the batch away. It would have been something so wildly unexpected that it would have been uselessly bewildering. Why, in the controlled environments that characterize science, do serendipitous discoveries of reasonably unexpected phenomena take place? When we speak of “control,” we use a concept that is devoid of any diachronic connotations (McBirnie,
The Antinomies of Serendipity
9
2008). It is not that control refers to things that are out of time, but either refers to preventing a process from developing, or to something that must be “sternly applied” onto something else: either you are in control, or you are not. The very idea of control is an abstraction as an act of removal, a concept that suppresses things that are true: for instance, the fact that in the course of time some events might escape our strictest control, because we are not Laplace’s demon, we have no exact computation of the future state of the world given an exact knowledge of the current conditions. Thus, what do we actually do when we exert control over something? We anticipate. As resumed by Poli (2010), anticipation concerns higher cognitive performances (when you make an elaborate forecast and behave consequently), lesser ones (driving is a matter of constant anticipation of the other drivers’ behaviors), and hard-wired reactions (bracing for an impact is a form of anticipation). Moreover, cognitive systems are anticipatory systems in Rosen’s sense: An anticipatory system is a system containing a predictive model of itself and/or its environment, which allows it to change state at an instant in accord with the model’s predictions pertaining to a later instant (Rosen, 1985, p. 341)
Anticipatory systems range from very complicated to very simple ones, the common denominator is their ability to make a more or less explicit forecast about future states of affairs and let these forecasts influence their current state in order to improve their performances. Cognition, as a system affected by beliefs, knowledge, and ignorance, is anticipatory in the sense that the very fact of understanding a perceived state of affairs as meaningful depends on the range of possible outcomes anticipated at an earlier stage. The change of state described by Rosen does not need to be an action: a cognitive change of state, for instant going from surprise to doubt (as the one performed by Fleming), is a change of state that can be acknowledged as the result of an anticipation. Ignorance, whose correct handling is vital for science, plays again a crucial role in determining the reach of our anticipation. Explicitly, according to our awareness about our ignorance (that is, in serendipity cases, the deepness of our investigative ignorance), we can project a range of anticipated events. But also the more extensive, unaware part of our ignorance shapes our possibility to anticipate. Anticipation can be more or less steady, we can anticipate with greater or lesser accuracy. Part of our anticipatory range can be clear: an experiment may lead to a series of likely, clearly anticipated outcomes, but also to other outcomes that are less anticipated – they are not expected, but once they take place, we realized they were implicitly expected. In other words, we did not know we were, but we are indeed able to deal with them – possibly, to recognize them as something new an relevant. Thus, anticipation can help us frame again serendipity while turning further away from the idea of luck. Or better. The idea of luck in the context of serendipitous discoveries can be drawn back to that of implicit anticipation. Luck, in these cases, means that something happens, and the scientist is able to grasp it as meaningful because she can change her cognitive state and so make room for the new, serendipitous event. This depends of course on the scientist’s training and how she manages her own ignorance. A dogmatic approach about one’s ignorance – which is the opposite of the
10
investigative ignorance and leads to think that “If there’s something I don’t know then that thing is irrelevant” – will hardly get her to any serendipitous discovery, because such a mindset leaves very little room available for implicit anticipation. As already argued, a mind open to doubt (a “prepared mind” in the words of Pasteur (1937, p. 131)), is the ideal scientific mind, reminiscent of the Socratic tradition: eager to acknowledge one’s ignorance in order to overcome at least part of it. The prepared mind is about attitude and not only about content: that is why the prepared mind is more likely to “get lucky:” it’s about the quality of its anticipatory range. At this point, it is easy to understand why multi-disciplinary teams (or a multidisciplinary training) are more likely to make serendipitous discoveries (as discussed by Darbellay et al. (2014)): the multiplicity of frameworks opens up a multiplicity of anticipatory ranges, both explicit and implicit and we can speak about an actual “multi-agent anticipation”. An analogy can be of help to understand the different levels of serendipity. Science is a bit like being in a jungle, at night, hunting for a specific kind of prey. You have a flashlight cutting through the night: part of the bushes and trees are illuminated directly by the flashlight, and things can pop-up before your eyes and you might recognize them as important. But things might be swarming slightly outside of your cone of light, where there is just a tiny reverberation. As an experienced hunter or wanderer, you can become aware of things that happen out of the main focus. Last but not least, it is easy to think that a hunting party will hunt more prey than a single hunter, not only because there will be different cones of light, meaning different anticipations, but also different kinds of light altogether. Many authors have dealt with the opportunity to increase the occurrence of serendipitous discoveries.4 Still, we can already frame that issue in terms of the anticipatory root of serendipity. Anticipation is a forward-looking activity. It relates to the future, to the extent that certain scholars compared anticipation to futuremaking. The relationship to be considered is the one between anticipation and selffulfilling prophecies. Self-fulfilling prophecies may happen in certain domains that are easier to influence, such as politics, economics or in general human affairs. A self-fulfilling prophecy in science is harder to come upon: there have been instances of artifacts created by the intense will to corroborate a given hypothesis, but if that is not the case the artifact will eventually be debunked. That is to say that, from the understanding of serendipity as a result of anticipation, the only way of making serendipitous discoveries more frequent is to work on the “prepared mind(s)”. Having assessed the cognitive dynamics that prepare the trigger of any serendipitous event, in the next section we will discuss the trait that defines serendipity in
4
Some authors proposed to increase the occurrence of serendipity in particular frameworks, especially in science, by augmenting the disciplinary specialization of the involved agents (Thagard, 1998), by improving and encouraging their social and interactional skills (Copeland, 2017), by opening the research to interdisciplinary explorations (Darbellay et al., 2014), or by creating a rich cognitive environment (McCay-Peet and Toms, 2015) – while it is widely acknowledged the accidental occurrence of these events and their perception is tied to a lack of control (Rubin et al., 2011).
The Antinomies of Serendipity
11
scientific contexts, that is the game-changing trait, by considering its inferential structure.
3 Serendipity: A Game-Changing Trigger or a Game-Changing Sensor? The third feature of serendipity, which defines it as a game-changing event or process, is specifically related to the scientific framework. In fact, serendipity (as a positive and chance-driven event or process) is discussed also in information and communication studies, where it mainly defines the “encountering or stumbling upon information when not directly looking for it [. . . ] often drawing a reaction of happiness, surprise or simply an aha! moment (and, sometimes, disappointment as well)” (Agarwal, 2015, p. 1). Notwithstanding the fact that in these contexts it still defines a “discovery made by chance”, this meaning of serendipity cannot be used in the scientific framework, since it targets a broader and less specific range of discoveries. The findings of new or useful information happen all the time in scientific or academic areas and cannot emphasize the exceptional value of the breakthroughs that usually are taken as examples of serendipity in science (such as Fleming’s, Maxwell’s, etc.).5 To serendipitously discover something in science means to perform more than a timely observation or a lucky guess: serendipity in this context defines those events that, emerging in the performance of ordinary scientific practice, turn around the target of an experiment, or change the observer’s perspective regarding the relevance of some objects, numerical values, or pieces of equipment. A major transformation happens, both epistemological and cognitive, which can be summarized with the so-called “Pasteur Principle”, ideated by Austin (2003, p. 76): “Some special receptivity born from past experience permits you to discern a new fact or to perceive ideas in a new relationship, and go on to comprehend their significance”. This dramatic change of prospect affects the explanations, theoretical viewpoints, and epistemic horizons constructed by scientists. 5
Even if the tag of serendipity in science is mainly used to describe deep perspectival changes, the game-changing condition may appear too strong to some ears for good reasons. Serendipity in the ordinary lexicon stands for both micro and macro findings that were unexpected but welcome to the finders eyes. These serendipitous moments occur often in both scientific and lay environments. Nonetheless, in this article we mean to focus on how serendipity affects the creative processes in science, which means to look for those serendipitous events that not only imply the scientists’ conscious acknowledgement of a lack of knowledge, but those that occur when the research community is firmly wed to an assumption or conclusion that is not true. This form of ignorance is especially troublesome since it implies that what the scientific community ”knows” is not true and has set it on the wrong path. The cases of serendipity that lead to adjust the viewpoint of the scientific community are those that we are interested in since they affect or guide the creative reasoning in the scientific progress. With this emphasis we do not mean to describe cases of micro serendipity as not worthy of attention, but we need to highlight that they have little or no role in the development of creative reasoning in science.
12
Moreover, the game-changing feature is often seen just retroactively (Copeland, 2015; Campanario, 1996; Baumeister et al., 2010): a serendipitous moment is recognized just post-hoc and it is vaguely deemed as either the beginning of the change of perspective or its conclusive outcome. Thus, the game-changing trait of serendipity both highlights a specific nuance of serendipitous discoveries in science and makes them more difficult to understand with respect to those made in information and communication studies. The struggle in the comprehension can be addressed by questioning how and when the game changes for the involved scientist. In few words: does serendipity mark the trigger for the change of perspective or is it just a post-hoc sensor of it? In order to tackle this question we need to refer again to the investigative ignorance – as it is called by Haas and Vogt (2015) – that is implied in a serendipitous discovery. Indeed, the moment of doubt, that emerges when confronting an unexpected situation, has been variously referenced to trigger a particular inferential process that has been also occasionally connected to the concept of serendipity: abduction (first and foremost by Peirce (1958b), then by Hookway (1998); Woods (2005); Magnani (2009); Arfini (2016)). In the words of Peirce: A mass of facts is before us. We go through them. We examine them. We find them a confused snarl, an impenetrable jungle. We are unable to hold them in our minds. We endeavor to set them down upon paper; but they seem so multiplex intricate that we can neither satisfy ourselves that what we have set down represents the facts, nor can we get any clear idea of what it is that we have set down. But suddenly, while we are poring over our digest of the facts and are endeavoring to set them into order, it occurs to us that if we were to assume something to be true that we do not know to be true, these facts would arrange themselves luminously. That is abduction. [. . . ]. (Peirce, 1958a, footnote 12, pp. 531-532).
Abduction incorporates in a word different aspects that are usually taken in consideration for the research on serendipity. It is an explanatory and ampliative inference (non-monotonic inference, logically speaking) that deals with ignorance problems (Woods, 2009; Magnani, 2017) by tentatively extending the knowledge of the cognitive agents through the examination and testing of particular hypotheses. It has been used in order to investigate the structure of both scientific and ordinary ampliative reasoning, and it is connected to the analysis of creativity, invention, and discovery. Thus, it is not so surprising to see it cited in the serendipity literature. As Darbellay et al. state: Discoveries through serendipity are thus associated with the type of reasoning that Peirce (1839–1914) called abduction, which complements deduction and induction. Abduction involves a more intuitive and exploratory way of reasoning, which allows one to provide the best explanation possible of a surprising and unexpected fact (Peirce, 1958b). The approach is similar to the “detective’s method,” in Umberto Eco’s sense (Eco, 1992, p. 272), through which the researcher, when confronted with a series of apparently unconnected facts, tries to confer on them an overall intelligibility by assembling them in a coherent sequence. (Darbellay et al., 2014, p. 4)
Nevertheless, even if abduction has been variously referred as one of the inferential structures that make serendipity emerge (Merton and Barber, 2010; Darbellay et al., 2014; McCay-Peet and Wells, 2017), the scholars who claimed it did not give
The Antinomies of Serendipity
13
much detail on how we can establish the connection between serendipity and abduction. Unfortunately, indeed, if it is true that not every time an information is casually discovered in science we can claim it a case of serendipity, it is also true that not every time an agent performs an abduction it can be considered a serendipitous event. Abduction is an explanatory reasoning based on hypotheses that can take many forms, from both a logical and an epistemological perspective. Formalized representations of abduction have been presented in the last forty years by various authors. Just to mention some of the most important ones we need to cite the AKMschema (which refer to the works of Aliseda (1997, 2006), Kowalski (1979), Kuipers (1999), (Kakas et al., 1992), Magnani (2001), and Meheus et al. (2002)) the G-W schema, which emphasizes the ignorance-preserving trait of abduction (and refers to the name of the creators, Gabbay and Woods (2005)) and the recent EC-Model (Eco-Cognitive Model) of abduction (Magnani, 2015, 2016). Also from a cognitive point of view, abduction has been variously classified: for example on the base of the epistemological format of the inference (sentential, model-based, through a thinking-through-doing manipulation); with respect to the fact that the hypothesis abduced is selected from one array of possibilities or created anew (which respectively describe selective abductions and creative ones); by considering the conscious or unconscious effort of the cognitive agent in performing the inference (e.g. perception highly relies on the performance of unconscious visual abductions), etc. The point is: if by referencing to the inferential structure of abduction we could grasp some specifics on how serendipity change the scientists perspective on their research, we should first specify which kind of abduction we can connect to cases of serendipitous discovery. A particular description which can help establishing the type of abduction we can easily connected to serendipity is offered by Hendricks and Faye (1999): New theoretical concepts can be introduced transcending the current body of background knowledge while yet others remain within the given understanding of things. A case in point would be the formulation of the hypothesis of electron spin. Bohr considered the spin conjecture as a welcome supplement to the current magnetic core theory. Pauli remained rather skeptical pertaining to the spin hypothesis due to the fact that it actually required the theory of quantum mechanics for its proper justification, which was not part of the background knowledge at the time of the conjecture. In such cases two paradigms are competing and the abduction is then dependent upon whether the conjecture is made within the paradigm or outside it. Hence distinguish between paradigmatic and trans-paradigmatic abduction. (Hendricks and Faye, 1999, p. 287)
Trans-paradigmatic abduction is basically a concept that defines the possibility to leap from one array of explanatory ideas to another by examining and discussing a compelling hypothesis that belongs to the latter. Thus, we could use the concept of trans-paradigmatic abduction to explain why in many examples of serendipitous discovery in science there is a retroactive recognition of the game-changing event while it is quite difficult to establish when or how it happened. For example, we can consider the case of Barry Marshall and Robin Warren, who proposed the theory that peptic ulcers are caused by bacterial infections after having discovered a new kind of bacteria in the stomachs of people with gastritis. As Thagard (1998, p. 114) states, “The discovery of Helicobacter pylori, and the formation
14
of the hypothesis that it routinely colonizes human stomachs, are the result of a combination of serendipity, questioning, and search.” This hypothesis was initially rejected by the medical community because the stomach was previously believed to be a sterile environment where bacteria could not survive long enough to damage it. Thus the generation of the hypothesis (which emerged from a lucky observation that led to a series of them) did not just provide a new explanation for the phenomenon of peptic ulcers, but a new viewpoint on the biological composition and balance of the stomach. This new point of view has been initially proposed when the inference was generated to make reason for an observation that could not be explained within the previous theoretical framework. In that moment the trans-paradigmatic abduction, generated by serendipity, operated the gamechanging switch that post hoc has been recognized by the medical community when referring to that serendipitous process. At the same time, without the proposing of the hypothesis, the serendipitous observation could not be made: thus, the transparadigmatic abduction was part of the serendipitous process as well as the lucky observation that initiated all of it. Therefore, the questions regarding how and when serendipity becomes a gamechanging process can be addressed by considering the structure of the trans-paradigmatic abduction that scientists operate to make sense of new and unexpected observations. As many authors in the literature of abduction affirm, the mere consideration of the new hypothesis does not initiate the process of abduction: the agent needs to cognitively and epistemically invest in the hypothesis, actually embracing it, in order to claim that the inferential process have been conducted (Gabbay and Woods, 2005). Thus, the conjunction of the lucky observation, the elaboration of the transparadigmatic abduction, and its testing composes the game-changing serendipitous process, which obviously can be recognized only retroactively when the emerging paradigm has been effectively established. In a formula, it is both a trigger that initiates a game-changing event and the sensor that the game has changed, at least for the scientist(s) who made the observation.
4 Concluding Remarks The aim of this article was to discuss the cognitive features of serendipity in scientific contexts, such as its yielding positive results, its game-changing trait, and its unexpected occurrence. All these traits described a problematic, almost paradoxical, depiction of serendipity, which defies its generic assimilation to the concepts of luck, control, and standard inferential reasoning. Thus, in the first section we commented the connection between the notions of serendipity and luck, deeming the former not reducible to the latter due to the active role that the agent must play in order to perform a serendipitous discovery. The agent needs to get in a state of “investigative ignorance” and doubt in order to take advantage of a serendipitous situation, while the mere luck requires just a focused interest by the involved agent. The active role of the agent in the generation of a
The Antinomies of Serendipity
15
serendipitous discovery brought us to discuss whether she can “prepare” to get in a similar situation. Indeed, while serendipity is a-priori unexpected, the concept of anticipation can explain why and how some discoveries have been made, or, more accurately, why some scientists were more prepared to discover something instead of ignoring anomalies in their plans. In the last section we broke down the inferential structure of serendipity in order to understand its game-changing trait in the scientific framework. By using the concept of trans-paradigmatic abduction, we described the performance of a serendipitous discovery as a way to leap from an epistemic domain to another in order to get a functional explanation which was not available in the former perspective.
References Agarwal, N. K. (2015). Towards a definition of serendipity in information behaviour. Information Research, 20(3):paper 675. Aliseda, A. (1997). Seeking Explanations: Abduction in Logic, Philosophy of Science and Artificial Intelligence. PhD thesis, Amsterdam: Institute for Logic, Language and Computation. Aliseda, A. (2006). Abductive Reasoning. Logical Investigations into Discovery and Explanation. Synthese Library: Volume 330. Springer, Berlin. Allen, C. M., Erdelez, S., and Marinov, M. (2013). Looking for opportunistic discovery of information in recent biomedical research: A content analysis. Proceedings of the American Society of Information Science and Technology, 50(1):1–22. Arfini, S. (2016). Thought experiments as model-based abductions. In Magnani, L. and Casadio, C., editors, Model-Based Reasoning in Science and Technology. Logical, Epistemological, and Cognitive Issues. Springer International Publishing, Switzerland. Austin, J. H. (2003). Chase, Chance, and Creativity: The Lucky Art of Novelty. The MIT Press, Cambridge, MA. Baumeister, A. A., Hawkins, M. F., and L´opez-Mu˜noz, F. (2010). Toward standardized usage of the word serendipity in the historiography of psychopharmacology. Journal of the History of the Neurosciences, 4(1):91–98. Brown, J. S. (1994). The Serendipitous Effects of Disaster Management by NonProfit Organizations: Study Cases in Jamaica, Costa Rica and Dominican Republic. Society for Applied Anthropology Annual Meeting, Cancun. Brown, J. S. (2010). Shaping serendipity. Highlight from collaborative innovation and a pull economy (entire talk). Retrived from https://ecorner.stanford.edu/inbrief/shaping-serendipity/. Campanario, J. (1996). Using citation classics to study the incidence of serendipity in scientific discovery. Scientometrics, 37(1):3–24. Cannon, W. B. (1940). The role of chance in discovery. The Scientific Monthly, 50(3):204–209. Catellin, S. (2014). S´erendipit´e. Du conte au concept. Seuil, Paris.
16
Cellucci, C. (2017). Rethinking Knowledge. The Heuristic View. Springer, Cham. Copeland, S. (2015). The Case of the Triggered Memory: Serendipitous Discovery and the Ethics of Clinical Research. PhD Thesis: Dalhousie University, Department of Philosophy. Retrived from https://dalspace.library.dal.ca/handle/10222/63140. Copeland, S. (2016). Was Fleming’s discovery of penicillin a paradigmatic case of serendipity, or not? In Article presented at the Conference: Nordic Network for Philosophy of Science 4th Annual Meeting, At Parnu, Estonia. Copeland, S. (2017). On serendipity in science: Discovery at the intersection of chance and wisdom. Synthese, pages 1–22. Online First. Darbellay, F., Moody, Z., Sedooka, A., and Steffen, G. (2014). Interdisciplinary research boosted by serendipity. Creativity Research Journal, 26(1):1–10. Eco, U. (1992). Les limites de l’interpr´etation. Grasset, Paris. Foster, A. and Ford, N. (2003). Serendipity and information seeking: An empirical study. Journal of Documentation, 59(3):321–340. Gabbay, D. M. and Woods, J. (2005). The Reach of Abduction: Insight and Trial, volume 1 of A Practical Logic of Cognitive Systems. Elsevier, Amsterdam: North Holland. Gillies, D. (2015). Serendipity and chance in scientific discovery: Policy implications for global society. In Archibugi, D. and Filippetti, A., editors, The Handbook of Global Science, Technology, and Innovation, pages 525–539. Wiley Blackwell, UK. Haas, J. and Vogt, K. M. (2015). Ignorance and investigation. In Gross, M. and McGoey, L., editors, Routledge International Handbook of Ignorance Studies, pages 17–24. Routledge, Abingdon. Hendricks, F. V. and Faye, J. (1999). Abducting explanation. In Magnani, L., Nersessian, N. J., and Thagard, P., editors, Model-Based Reasoning in Scientific Discovery, pages 271–294. Kluwer Academic/Plenum Publishers, New York. Hookway, C. (1998). Doubt: Affective states and the regulation of inquiry. Canadian Journal of Philosophy, 28(1):203–225. Ippoliti, E. (2017). Scientific discovery reloaded. Topoi. DOI: 10.1007/s11245017-9531-3. Kakas, A., Kowalski, R. A., and Toni, F. (1992). Abductive logic programming. Journal of Logic and Computation, 2(6):719–770. Kakko, I. and Inkinen, S. (2009). Homo creativus: Creativity and serendipity management in third generation science and technology parks. Science & Public Policy, 36(7):537–548. Kantorovich, A. K. (1993). Scientific Discovery: Logic and Tinkering. SUNY Press, New York. Kantorovich, A. K. (2016). Serendipity: An Ecologist’s Quest to Understand Nature. University of California Press, Berkeley. Kipnis, N. (2005). Chance in science: The discovery of electromagnetism by H.C. Oersted. Science & Education, 14(1):1–28. Kowalski, R. A. (1979). Logic for Problem Solving. Elsevier, New York.
The Antinomies of Serendipity
17
Kuipers, T. A. F. (1999). Abduction aiming at empirical progress of even truth approximation leading to a challenge for computational modelling. Foundations of Science, 4(3):307–323. Magnani, L. (2001). Abduction, Reason, and Science. Processes of Discovery and Explanation. Kluwer Academic/Plenum Publishers, New York. Magnani, L. (2009). Abductive Cognition. The Epistemological and Eco-Cognitive Dimensions of Hypothetical Reasoning. Springer, Berlin/Heidelberg. Magnani, L. (2015). The eco-cognitive model of abduction. >Apagwg now: Naturalizing the logic of abduction. Journal of Applied Logic, 13:285–315. Magnani, L. (2016). The eco-cognitive model of abduction. Irrelevance and implausibility exculpated. Journal of Applied Logic, 15:94–129. Magnani, L. (2017). The Abductive Structure of Scientific Creativity. An Essay on the Ecology of Cognition. Springer, Switzerland. McBirnie, A. (2008). Seeking serendipity: The paradox of control. ASLIB Proceedings, 60(6):600–618. McCay-Peet, L. and Toms, E. (2015). Investigating serendipity: How it unfolds and what may influence it. Journal of the Association for Information Science and Technology, 66(7):1463–1476. McCay-Peet, L. and Wells, P. (2017). Serendipity in the sciences: Exploring the boundaries. Proceedings of the Nova Scotian Institute of Science (PNSIS), 49(1):97–116. Meheus, J., Verhoeven, L., Van Dyck, M., and Provijn, D. (2002). Ampliative adaptive logics and the foundation of logic-based approaches to abduction. In Magnani, L., Nersessian, N. J., and Pizzi, C., editors, Logical and Computational Aspects of Model-Based Reasoning, pages 39–71. Kluwer Academic Publishers, Dordrecht. Merton, R. K. and Barber, E. (2010). The Travels and Adventures of Serendipity: A Study in Sociological Semantics and the Sociology of Science. Princeton University Press, Princeton, NJ. Morris, K. (2012). Epistemic luck. British Journal for Philosophy of Science, 63(1):357–371. Pasteur, L. (1854/1937). Oeuvres compl´etes r`eunies par M. Pasteur Vallery-Radot, M`elanges scientifiques et litt`eraires. Masson et Cie Editeurs, Paris. Pasteur, L. (1883/1922). Oeuvres compl´etes r`eunies par M. Pasteur Vallery-Radot, Dissym`etrie mol`eculaire. Masson et Cie Editeurs, Paris. Peirce, C. S. (1931-1958a). Pragmatism as the logic of abduction. In Hartshorne, C. and Weiss, P., editors, Collected Papers of Charles Sanders Peirce. Harvard University Press, Cambridge. Peirce, C. S. (1931-1958b). Collected Papers of Charles Sanders Peirce. Harvard University Press, Cambridge, MA. vols. 1-6, Hartshorne, C. and Weiss, P., eds.; vols. 7-8, Burks, A. W., ed. Peirce, C. S. (1998). The fixation of belief. In Houser, N. and Kloesel, C., editors, The Essential Peirce Selected Philosophical Writing, volume 1, (1867-1893). Indiana University Press, Indiana. Poli, R. (2010). The many aspects of anticipations. Foresight, 12(3):7–17.
18
Pritchard, D. (2004). Epistemic luck. Journal of Philosophical Research, 29(1):193–222. Ranalli, C. (2013). Luck, propositional perception, and the entailment thesis. Synthese, 191(6):1223–1247. Roberts, R. M. (1989). Serendipity: Accidental Discoveries in Science. Wiley, New York. Rohwer, Y. (2014). Lucky understanding without knowledge. Synthese, 191(5):945–959. Rosen, R. (1985). Anticipatory Systems. Philosophical, Mathematical and Methodological Foundations. Pergamon Press, Oxford. Rosenman, M. F. (1988). Serendipity and scientific discovery. The Journal of Creative Behavior, 22(2):132–138. Rubin, V., Burkell, J., and Quan-Haase, A. (2011). Facets of serendipity in everyday chance encounters: a grounded theory approach to blog analysis. Information Research, 16(3):paper 488. Slowiczek, F. and Peters, P. M. (2007). Discovery, chance, and the scientific method. Access Excellence Classic Collection. Retrived from http://www.accessexcellence.org/AE/AEC/CC/chance.html. Thagard, P. (1998). Ulcers and bacteria I: Discovery and acceptance. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biology and Biomedical Science, 29(1):107–136. Van Andel, P. (1994). Anatomy of the unsought finding. serendipity: Origin, history, domains, traditions, appearances, patterns and programmability. British Journal for the Philosophy of Science, 45(2):631–648. Walpole, H. (1789). Letter to Mrs. More. In Private Correspondance of Horace Walpole, volume IV (Ed. 1820). Rodwell and Martin, London. Woods, J. (2005). Epistemic bubbles. In Artemov, S., Barringer, H., Garcez, A., Lamb, L., and Woods, J., editors, We Will Show Them: Essay in Honour of Dov Gabbay (Volume II). College Pubblications, London. Woods, J. (2009). Ignorance, inference and proof: abductive logic meets the criminal law. In Tuzet, G. and Canale, D., editors, The Rules of Inference: Inferentialism in Law and Philosophy. Egea, Italy.
