Researching Serendipity in Digital Information Environments. Lori McCay-Peet

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      4. Incubation, consumption, and follow-up time is a factor in all phenomena described as serendipitous, and it is this factor which exacerbates our ability to research serendipity. While we often delight in Archimedes “Eureka!” it is a rarity that an observation is made and a discovery is realized in the blink of an eye. There is a gestation period so that the anomaly or surprise can be explored, interpreted, and analyzed, as the case of the floppy ears attests; this aspect is typically attributed to the creative process (Herrmann, 1989). Pasteur was purported to have said “Let me tell you the secret that has led to my goal: my strength lies solely in my tenacity.”

      5. There is a valuable outcome. In the sciences, it may have global ramifications such as the discovery of penicillin, radioactivity and smart dust. But at the individual level, it may lead to a change in direction, or personal problem solved. It is in the outcome that the relationship between serendipity and creativity become apparent: “creativity involves coming up with something novel, something different. And, in order to be interesting, it must be something intelligible and must relate to that which we know before” (Boden, 1996, p. 165), but it most likely will be something that no one has thought of before (Shaprio, 1986). However, serendipity is not a mirror image of the creative process; serendipity is a divergent process that may also discover a problem (Campos and de Figueiredo, 2002) that does not fit the usual creative process.

      In summary, for an event, outcome or process to be serendipitous, it is initiated with an anomalous observation by a person who has the requisite skills to observe its irregularity, and the mental space to follow through on the observation, taking whatever requisite time is required to turn it into an unexpected finding. This is a time-tested process well documented in the physical world in science, medicine and technology in particular. This now serves as a basis for our examination of serendipity in digital information environments. Table 3.1 illustrates how five research groups who have studied serendipity in digital information environments have conceptualized the elements of serendipity primarily as a linear process, but influenced by additional elements. Chapter 4 shows how we have adapted the physical world perspective described above to the digital information environment.

1.3 HOW SERENDIPITY HAPPENS

      From the origins and use of the concept to date, three potential interpretations of how serendipity unfolds have emerged. They serve as a useful approach in understanding and deconstructing the process. Rather than enter that debate (e.g., is pseudo serendipity really serendipity?), we instead associate all three with serendipity although each has its supporters and naysayers. The three types are described below and illustrated in Figure 1.1. Examples are provided for each, all drawn from the sciences because they provide concrete illustrations of the three ways serendipity has been described to date. These types will be further explored specifically in relation to digital information environments in Chapter 4.

      • Type A. From Observations to Solution

      An individual makes an observation that leads to the discovery of something novel; neither the observation nor the outcome is the objective of the investigation. This was the basis on which Walpole created the concept. In his description of the tale, the three princes were not looking for anything; they were able to solve a problem once they were presented with the clues. This has been described as abduction—“a form of reasoning to discover something new” (as discussed in Van Andel, 1994, p. 636), but regardless of the reasoning process, Type A meets the five conditions discussed in Section 1.2.

      Examples:

      ° When Spencer stood near a magnetron, a vacuum tube that generates microwaves to boost the sensitivity of radar, he noted an odd sensation; the chocolate bar in his pocket had melted, and a bag of popcorn popped. A year later he had patented the technology for a microwave oven (e.g., Leslie, 2012);

      ° George de Mestral was out walking his dog when he noted the prickly seeds from shrubs that got caught in the fabric of his clothes, which led him to wonder why which they stick, and after investigation to go on to invent Velcro (e.g., Pease et al., 2013)

      Neither reportedly set out to solve the problems; they made astute observations which when combined with their own knowledge led to surprise outcomes.

      • Type B. From Problem I to a Solution for Problem II

      In this variation, an individual is looking for a solution to a problem, but instead finds a solution to another problem. This is the interpretation of Solly and the literary scholars of the 19th century (and it was interpretation that was first quoted in the Oxford English Dictionary in 1913) and continues to be perhaps the most popular interpretation today.

      Examples:

      ° Fleming was growing Staphylococcus bacteria in a petri dish when it became contaminated with a spore of Penicilliusm fungus. His deep understanding of bacteria (his sagacity) led him to observe how the mold in his petri dish killed the surrounding bacteria, and thus led to one of the most important advancements in health in the early 20th century (e.g., Roberts, 1989);

      ° Art Fry was trying to develop a superglue when he accidentally devised a very weak glue that enabled two pieces of paper to be pried apart which led to development of Post-it Notes (e.g., Pease et al., 2013).

      In both these cases, the researchers were working diligently on a particular problem when an observation led them in a different direction, resulting in a novel solution to a problem that they had not initially intended to solve.

      • Type C. Unexpected Solutions

      An individual is looking for a solution to a particular problem, but the solution does not come from expected sources. The solution discovered by accident is found in an unusual or surprising way that could not have been predicted at the outset. This has also been called pseudo-serendipity (Roberts, 1989).

      Example:

      ° Goodyear was seeking a solution to the problem of rubber. In winter it hardened, while in summer it melted. As the story goes, he accidentally dropped rubber on a stove and observed on cooling that it turned into a charred leather-like substance with an elastic rim. From this unexpected event, he invented vulcanized rubber that is still in use today (e.g., Halacy, 1967).

      Serendipity Types A, B, and C share common features as illustrated in Figure 1.1. In their examination of serendipity, de Figueiredo and Campos (2001) provide a parsimonious mathematical notation to describe each. The types are typically distinguished by whether there was intent to solve a problem or find a solution to a new or existing problem (Napier and Vuong, 2013; Foster and Ford, 2003; Cunha et al, 2014; De Rond, 2014). All types emerge out of a context, which may be any work or pleasure environment, with variable starting points, and all get to a solution; if this were the only ingredients, then we would be dealing with ordinary problem-solving. What distinguishes these types from ordinary problem solving are the two key points in the process:

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