I define serendipity as the art of making an unsought finding. And I propose an overview of my collection of serendipities, the largest yet assembled, chiefly in science and technology, but also in art, by giving a list of ‘serendipity patterns’. Although my list of ‘patterns’ is just a list and not a classification, it serves to introduce a new and possibly stimulating perspective on the old subject of serendipity. Knowledge of these ‘serendipity patterns’ might help in expecting also the (...) unexpected and in finding also the unsought. * I acknowledge A. D. de Groot, R. C. M. Noordam, B. P. van Heusden, T. Pinkster, C. J. van den Berg, T. A. F. Kuipers, A. Wegener Sleeswijk and my referee for their suggestions and I dedicate this article to T. A. van Kooten. Cases and studies of serendipidy are welcome. À propos: a travelling serendipity exhibition is available, also for ‘new democracies’: ‘Freedom of opportunity as developed by democracy is the best human reaction to divergent phenomena. We may, in fact, define ‘freedom’ as ‘the opportunity to profit from the unexpected.’ (Langmuir [1956]). (shrink)

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. (shrink)

The way scientific discovery has been conceptualized has changed drastically in the last few decades: its relation to logic, inference, methods, and evolution has been deeply reloaded. The ‘philosophical matrix’ moulded by logical empiricism and analytical tradition has been challenged by the ‘friends of discovery’, who opened up the way to a rational investigation of discovery. This has produced not only new theories of discovery, but also new ways of practicing it in a rational and more systematic way. Ampliative rules, (...) methods, heuristic procedures and even a logic of discovery have been investigated, extracted, reconstructed and refined. The outcome is a ‘scientific discovery revolution’: not only a new way of looking at discovery, but also a construction of tools that can guide us to discover something new. This is a very important contribution of philosophy of science to science, as it puts the former in a position not only to interpret what scientists do, but also to provide and improve tools that they can employ in their activity. (shrink)

One of the key supposed 'platitudes' of contemporary epistemology is the claim that knowledge excludes luck. One can see the attraction of such a claim, in that knowledge is something that one can take credit for - it is an achievement of sorts - and yet luck undermines genuine achievement. The problem, however, is that luck seems to be an all-pervasive feature of our epistemic enterprises, which tempts us to think that either scepticism is true and that we don't know (...) very much, or else that luck is compatible with knowledge after all. In this book, Duncan Pritchard argues that we do not need to choose between these two austere alternatives, since a closer examination of what is involved in the notion of epistemic luck reveals varieties of luck that are compatible with knowledge possession and varieties that aren't. Moreover, Pritchard shows that a more nuanced understanding of the relationship between luck and knowledge can cast light on many of the most central topics in contemporary epistemology. These topics include: the externalism/internalism distinction; virtue epistemology; the problem of scepticism; metaepistemological scepticism; modal epistemology; and the problem of moral luck. All epistemologists will need to come to terms with Pritchard's original and incisive contribution. (shrink)

Pragmatists challenge a sharp separation of issues of theoretical and practical rationality. This can encourage a sort of anti-realism: our classifications and theories are shaped by our interests and practical concerns. However, it need not do this. A more fundamental theme is that cognition is itself an activity, the attempt to solve problems and discover truths effectively and responsibly. Evidence has to be collected, experiments have to be devised and carried out, dialogues must be engaged in with fellow inquirers, decisions (...) must be made about when we have scrutinized our opinions enough to trust our results. Even if our goals are “purely cognitive,” the attempt to achieve them through inquiry and deliberation is an activity. The normative standards that guide its conduct, like those governing any activity, will include standards of practical rationality. Indeed, we might suggest that a belief isjustifiedso long as it is the product of responsible, well-executed inquiry. (shrink)

The main message of this volume is that the creative process of discovery is not a purely rational enterprise in the traditional sense which equates rationality with logical reasoning, yet it is a manifestation of a universal phenomenon ...

Looking out the window, I see that it's raining outside. Do I know that it’s raining outside? According to proponents of the Entailment Thesis, I do. If I see that p, I know that p. In general, the Entailment Thesis is the thesis that if S perceives that p, S knows that p. But recently, some philosophers (McDowell 2002, Turri 2010, Pritchard 2011, 2012) have argued that the Entailment Thesis is false. On their view, we can see p and not (...) know that p. In this paper, I argue that their arguments are unsuccessful. (shrink)

“Probably Peirce’s best-known works are the first two articles in a series of six that originally were collectively entitled Illustrations of the Logic of Science and published in Popular Science Monthly from November 1877 through August 1878. The first is entitled ‘The Fixation of Belief’ and the second is entitled ‘How to Make Our Ideas Clear.’ In the first of these papers Peirce defended, in a manner consistent with not accepting naive realism, the superiority of the scientific method over other (...) methods of overcoming doubt and ‘fixing belief.’” — Robert Burch, “Charles Sanders Peirce,” entry in the Stanford Encyclopedia of Philosophy (2021 revision) -/- “Pragmatist epistemologies often explore how we can carry out inquiries in a self-controlled and fruitful way. (Where much analytic epistemology centres around the concept of knowledge, considered as an idealised end-point of human thought, pragmatist epistemology centres around the concept of inquiry, considered as the process of knowledge-seeking and how we can improve it.) So pragmatists often provide rich accounts of the capacities or virtues that we must possess in order to inquire well, and the rules or guiding principles that we should adopt. A canonical account is Peirce’s classic early paper ‘The Fixation of Belief‘. Here Peirce states that inquiry is a struggle to replace doubt with “settled belief“, and that the only method of inquiry that can make sense of the fact that at least some of us are disturbed by inconsistent beliefs, and will subsequently reflect upon which methods of fixing belief are correct is the Method of Science, which draws on the Pragmatic Maxim described above. This contrasts with three other methods of fixing belief: i) refusing to consider evidence contrary to one’s favored beliefs (the Method of Tenacity), ii) accepting an institution’s dictates (the Method of Authority), iii) developing the most rationally coherent or elegant-seeming belief-set (the A Priori Method).“ — Catherine Legg, “Pragmatism,” entry in the Stanford Encyclopedia of Philosophy (2021 revision). (shrink)

It is plausible to think that the epistemic benefit of having an explanation is understanding. My focus in this article is on the extent to which explanatory understanding, perhaps unlike knowledge, is compatible with certain forms of luck—the extent to which one can understand why something is the case when one is lucky to truly believe an explanatorily relevant proposition. I argue, contra Stephen Grimm ([2006]) and Duncan Pritchard ([2008], [2009]), that understanding quite generally is compatible with luckily believing a (...) true, explanatorily relevant proposition. My strategy is to argue that various intuitions that seem to rule against lucky understanding can be explained away, and thus do not compel us to reject the thesis that, in general, understanding tolerates luck. In arriving at this conclusion, I address some salient issues regarding the testimony of others, and also draw out the consequences of my discussions for the status of understanding as a cognitive achievement. (shrink)

This book employs a new eco-cognitive model of abduction to underline the distributed and embodied nature of scientific cognition. Its main focus is on the knowledge-enhancing virtues of abduction and on the productive role of scientific models. What are the distinctive features that define the kind of knowledge produced by science? To provide an answer to this question, the book first addresses the ideas of Aristotle, who stressed the essential inferential and distributed role of external cognitive tools and epistemic mediators (...) in abductive cognition. This is analyzed in depth from both a naturalized logic and an ecology of cognition perspective. It is shown how the maximization of cognition, and of abducibility – two typical goals of science – are related to a number of fundamental aspects: the optimization of the eco-cognitive situatedness; the maximization of changeability for both the input and the output of the inferences involved; a high degree of information-sensitiveness; and the need to record the “past life” of abductive inferential practices. Lastly, the book explains how some impoverished epistemological niches – the result of a growing epistemic irresponsibility associated with the commodification and commercialization of science – are now seriously jeopardizing the flourishing development of human creative abduction. (shrink)

‘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. (shrink)

The view that the subject matter of epistemology is the concept of knowledge is faced with the problem that all attempts so far to define that concept are subject to counterexamples. As an alternative, this article argues that the subject matter of epistemology is knowledge itself rather than the concept of knowledge. Moreover, knowledge is not merely a state of mind but rather a certain kind of response to the environment that is essential for survival. In this perspective, the article (...) outlines an answer to four basic questions about knowledge: What is the role of knowledge in human life? What is the relation between knowledge and reality? How is knowledge acquired? Is there any a priori knowledge? (shrink)

In this paper we address the classical but still pending question regarding Thought Experiments: how can an imagined scenario bring new information or insight about the actual world? Our claim is that this general problem actually embraces two distinct questions: how can the creation of a just imagined scenario become functional to either a scientific or a philosophical research? and how can Thought Experiments hold a strong inferential power if their structures “do not seem to translate easily into standard forms (...) of deduction or induction”? :534–541, 1999). We contend that, in order to answer both questions, we should consider the relation between the creation of the imagined scenario and the inferential power of Thought Experiments. Specifically, we will analyze Thought Experiments from an eco-cognitive point of view as goal-oriented objects, explaining their inferential power considering their generation as the result of abductive cognition and the construction of an imagined scenario as a process of scientific modeling. This will lead us to consider the creation of a Thought Experiment as a case of sophisticated model-based abduction. (shrink)

In 1983, Dr. J. Robin Warren and Dr. Barry Marshall reported finding a new kind of bacteria in the stomachs of people with gastritis. Warren and Marshall were soon led to the hypothesis that peptic ulcers are generally caused, not by excess acidity or stress, but by a bacterial infection. Initially, this hypothesis was viewed as preposterous, and it is still somewhat controversial. In 1994, however, a U. S. National Institutes of Health Consensus Development Panel concluded that infection appears to (...) play an important contributory role in the pathogenesis of peptic ulcers, and recommended that antibiotics be used in their treatment. Peptic ulcers are common, affecting up to 10% of the population, and evidence has mounted that many ulcers can be cured by eradicating the bacteria responsible for them. (shrink)

This paper primarily deals with theconceptual prospects for generalizing the aim ofabduction from the standard one of explainingsurprising or anomalous observations to that ofempirical progress or even truth approximation. Itturns out that the main abduction task then becomesthe instrumentalist task of theory revision aiming atan empirically more successful theory, relative to theavailable data, but not necessarily compatible withthem. The rest, that is, genuine empirical progress aswell as observational, referential and theoreticaltruth approximation, is a matter of evaluation andselection, and possibly new (...) generation tasks forfurther improvement. The paper concludes with a surveyof possible points of departure, in AI and logic, forcomputational treatment of the instrumentalist taskguided by the `comparative evaluation matrix''. (shrink)

Investigates the application of logic to problem solving and computer programming. Requires no previous knowledge in this field, and therefore can be used as an introduction to logic, the theory of problem-solving and computer programming. Annotation copyrighted by Book News, Inc., Portland, OR.

This book explores new findings on the long-neglected topic of theory construction and discovery, and challenges the orthodox, current division of scientific development into discrete stages: the stage of generation of new hypotheses; the stage of collection of relevant data; the stage of justification of possible theories; and the final stage of selection from among equally confirmed theories. The chapters, written by leading researchers, offer an interdisciplinary perspective on various aspects of the processes by which theories rationally should, and descriptively (...) are, built. They address issues such as the role of problem-solving and heuristic reasoning in theory-building; how inferences and models shape the pursuit of scientific knowledge; the relation between problem-solving and scientific discovery; the relative values of the syntactic, semantic, and pragmatic view of theories in understanding theory construction; and the relation between ampliative inferences, heuristic reasoning, and models as a means for building new theories and knowledge. Through detailed arguments and examinations, the volume collectively challenges the orthodox view’s main tenets by characterizing the ways in which the different “stages” are logically, temporally, and psychologically intertwined. As a group, the chapters provide several attempts to answer long-standing questions about the possibility of a unified conceptual framework for building theories and formulating hypotheses. (shrink)

Can one still have understanding in situations that involve the kind of epistemic luck that undermines knowledge? Kvanvig (The value of knowledge and the pursuit of understanding, 2003; in: Haddock A, Miller A, Pritchard D (eds) Epistemic value, 2009a; in: Haddock A, Miller A, Pritchard D (eds) Epistemic value, 2009b) says yes, Prichard (Grazer Philos Stud 77:325–339, 2008; in: O’Hear A (ed) Epistemology, 2009; in: Pritchard D, Millar A, Haddock A (eds) The nature and value of knowledge: three investigations, 2010) (...) say sometimes, DePaul and Grimm (Philos Phenomenol Res 74:498–514, 2007) and Grimm (Br J Philos Sci 57:515–535, 2006; in: Bernecker S, Pritchard D (eds) The Routledge companion to epistemology, 2011), Kvanvig’s critics, say no. The cases put forth by Kvanvig’s critics share a common feature, which seems to drive the intuition that understanding can’t be lucky: the fact that the information that makes up the individual’s understanding comes exclusively from a bad source. I formulate a case that lacks this feature, drawing on the fact that understanding produced from scientific inquiry is often produced by collaboration. I argue that my case provides good evidence that understanding is not a species of knowledge. (shrink)

Theoretical and manipulative abduction conjectures and manipulations : the extra-theoretical dimension of scientific discovery. -- Non-explanatory and instrumental abduction : plausibility, implausibility, ignorance preservation. -- Semiotic brains and artificial minds : how brains make up material cognitive systems. -- Neuromultimodal abduction : pre-wired brains, embidiment, neurospaces. -- Animal abduction : from mindless organisms to srtifactual mediators. -- Abduction, affordances, and cognitive niches : sharing representations and creating chances through cognitive niche construction. -- Abduction in human and logical agents : hasty (...) generalizers, hybrid abducers, fallacies. -- Morphodynamical abduction : causation of hypotheses by attractors dynamics. (shrink)

A personal story of the ways in which persistence, chance, and creativity interact in biomedical research. This first book by the author of Zen and the Brain examines the role of chance in the creative process. James Austin tells a personal story of the ways in which persistence, chance, and creativity interact in biomedical research; the conclusions he reaches shed light on the creative process in any field. Austin shows how, in his own investigations, unpredictable events shaped the outcome of (...) his research and brought about novel results. He then goes beyond this story of serendipity to propose a new classification of the varieties of chance, drawing on his own research and examples from the history of science—including the famous accidents that led Fleming to the discovery of penicillin. Finally, he explores the nature of the creative process, considering not only the environmental and neurophysiological correlates of creativity but also the role of intuition in both scientific discoveries and spiritual quests. This updated MIT Press paperback edition includes a new introduction and recent material on medical research, creativity, and spirituality. (shrink)