JOURNAL ARTICLES AND BOOK CHAPTERS
Forthcoming. “The Productive Anarchy of Scientific Imagination.” Philosophy of Science.
Imagination is important for many things in science: solving problems, interpreting data, designing studies, etc. Philosophers of imagination typically account for the productive role played by imagination in science by focusing on how imagination is constrained, e.g., by using self-imposed rules to infer logically, or model events accurately. But the constraints offered by these philosophers either constrain too much, or not enough, and they can never account for uses of imagination that are needed to break today’s constraints in order to make progress tomorrow. Thus, epistemology of imagination needs to make room for an element of epistemological anarchy.
Forthcoming. “Towards a Dual Process Epistemology of Imagination.” Synthese. DOI: 10.1007/s11229-019-02116-w.
Sometimes we learn through the use of imagination. The epistemology of imagination asks how this is possible. One barrier to progress on this question has been a lack of agreement on how to characterize imagination; for example, is imagination a mental state, ability, character trait, or cognitive process? This paper argues that we should characterize imagination as a cognitive ability, exercises of which are cognitive processes. Following dual process theories of cognition developed in cognitive science, the set of imaginative processes is then divided into two kinds: one that is unconscious, uncontrolled, and effortless, and another that is conscious, controlled, and effortful. This paper outlines the different epistemological strengths and weaknesses of the two kinds of imaginative process, and argues that a dual process model of imagination helpfully resolves or clarifies issues in the epistemology of imagination and the closely related epistemology of thought experiments.
Forthcoming. “P-Curving X-Phi: Does Experimental Philosophy Have Evidential Value?” Analysis. (With E. Machery and D. Colaço).
In this article, we analyse the evidential value of the corpus of experimental philosophy (x-phi). While experimental philosophers claim that their studies provide insight into philosophical problems, some philosophers and psychologists have expressed concerns that the findings from these studies lack evidential value. Barriers to evidential value include selection bias (i.e., the selective publication of significant results) and p-hacking (practices that in- crease the odds of obtaining a p-value below the significance level). To find out whether the significant findings in x-phi papers result from selection bias or p-hacking, we applied a p-curve analysis to a corpus of 365 x-phi chapters and articles. Our results suggest that this corpus has evidential value, although there are hints of p-hacking in a few parts of the x-phi corpus.
2019. “Everyday Scientific Imagination: A Qualitative Study of the Uses, Norms, and Pedagogy of Imagination in Science.” Science & Education 28(6), 711-730. DOI: 10.1007/s11191-019-00067-9.
Imagination is necessary for scientific practice, yet there are no in vivo sociological studies on the ways that imagination is taught, thought of, or evaluated by scientists. This article begins to remedy this by presenting the results of a qualitative study performed on two systems biology laboratories. I found that the more advanced a participant was in their scientific career, the more they valued imagination. Further, positive attitudes toward imagination were primarily due to the perceived role of imagination in problem-solving. But not all problem-solving episodes involved clear appeals to imagination, only maximally specific problems did. This pattern is explained by the presence of an implicit norm governing imagination use in the two labs: only use imagination on maximally specific problems, and only when all other available methods have failed. This norm was confirmed by the participants, and I argue that it has epistemological reasons in its favour. I also found that its strength varies inversely with career stage, such that more advanced scientists do (and should) occasionally bring their imaginations to bear on more general problems. A story about scientific pedagogy explains the trend away from (and back to) imagination over the course of a scientific career. Finally, some positive recommendations are given for a more imagination-friendly scientific pedagogy.
2019. “The Role of Imagination in Social Scientific Discovery: Why Machine Discoverers Will Need Imagination Algorithms.” Pp. 49-66 in M. Addis et al. (eds.), (2019). Scientific Discovery in the Social Sciences. Springer: Heidelberg.
When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them from such activity? A close look at the methodology of interpretive social science reveals several abilities necessary to make a social scientific discovery, and one capacity necessary to possess any of them is imagination. For machines to make discoveries in social science, therefore, they must possess imagination algorithms.
2019. “Peeking Inside the Black Box: A New Kind of Scientific Visualization.” Minds and Machines 29: 87–107. (With N. Nersessian).
Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization (observed in a qualitative study of a systems biology laboratory) that was developed to address just this sort of epistemic opacity. The visualization is unusual in that it depicts the dynamics and structure of a computer model instead of that model’s target system, and because it is generated algorithmically. Using considerations from epistemology and aesthetics, we explore how this new kind of visualization increases scientific understanding of the content and function of computer models in systems biology to reduce epistemic opacity.
2018. “The Content-Dependence of Imaginative Resistance.” Pp. 143-166 in F. Cova and S. Rénhault (eds.), Advances in Experimental Philosophy of Aesthetics. London: Bloomsbury. (With H. Kim and M. Kneer).
An observation of Hume’s has received a lot of attention over the last decade and a half: Although we can standardly imagine the most implausible scenarios, we encounter resistance when imagining propositions at odds with established moral (or perhaps more generally evaluative) convictions. The literature is ripe with ‘solutions’ to this so-called ‘Puzzle of Imaginative Resistance’. Few, however, question the plausibility of the empirical assumption at the heart of the puzzle. In this paper, we explore empirically whether the difficulty we witness in imagining certain propositions is indeed due to claim type (evaluative v. non-evaluative) or whether it is much rather driven by mundane features of content. Our findings suggest that claim type plays but a marginal role, and that there might hence not be much of a ‘puzzle’ to be solved.
2018. “How Thought Experiments Increase Understanding.” Pp. 526-44 in M. Stuart et al. (eds.), The Routledge Companion to Thought Experiments. London: Routledge.
We might think that thought experiments are at their most powerful or most interesting when they produce new knowledge. This would be a mistake; thought experiments that seek understanding are just as powerful and interesting, and perhaps even more so. A growing number of epistemologists are emphasizing the importance of understanding for epistemology, arguing that it should supplant knowledge as the central notion. In this chapter, I bring the literature on understanding in epistemology to bear on explicating the different ways that thought experiments increase three important kinds of understanding: explanatory, objectual and practical.
2018. “Thought Experiments: The State of the Art.” Pp. 1-28 in M. Stuart et al. (eds.), The Routledge Companion to Thought Experiments. London: Routledge.
This is the introduction for the Routledge Companion to Thought Experiments.
2017. “Imagination: A Sine Qua Non of Science.” Croatian Journal of Philosophy Vol. XVII, No. 49: 9-32.
What role does the imagination play in scientific progress? After examining several studies in cognitive science, I argue that one thing the imagination does is help to increase scientific understanding, which is itself indispensable for scientific progress. Then, I sketch a transcendental justification of the role of imagination in this process.
2016. “Norton and the Logic of Thought Experiments.” Axiomathes 26: 451–466.
John D. Norton defends an empiricist epistemology of thought experiments , the central thesis of which is that thought experiments are nothing more than arguments. Philosophers have attempted to provide counterexamples to this claim, but they haven’t convinced Norton. I will point out a more fundamental reason for reformulation that criticizes Norton’s claim that a thought experiment is a good one when its underlying logical form possesses certain desirable properties. I argue that by Norton’s empiricist standards, no thought experiment is ever justified in any deep sense due to the properties of its logical form. Instead, empiricists should consider again the merits of evaluating thought experiments more like laboratory experiments , and less like arguments.
2016. “Taming Theory with Thought Experiments: Understanding and Scientific Progress.” Studies in the History and Philosophy of Science Part A 58: 24-33. (This paper was highlighted in Nature Physics here).
I claim that one way thought experiments contribute to scientific progress is by increasing scientific understanding. Understanding does not have a currently accepted characterization in the philosophical literature, but I argue that we already have ways to test for it. For instance, current pedagogical practice often requires that students demonstrate being in either or both of the following two states: 1) Having grasped the meaning of some relevant theory, concept, law or model, 2) Being able to apply that theory, concept, law or model fruitfully to new instances. Three thought experiments are presented which have been important historically in helping us pass these tests, and two others that cause us to fail. Then I use this operationalization of understanding to clarify the relationships between scientific thought experiments , the understanding they produce, and the progress they enable. I conclude that while no specific instance of understanding (thus conceived) is necessary for scientific progress, understanding in general is.
2015. “Philosophical Conceptual Analysis as an Experimental Method.” Pp. 267-292 in Gamerschlag et al. (eds.). Meaning, Frames and Conceptual Representation. Düsseldorf: Düsseldorf University Press.
Philosophical conceptual analysis is an experimental method. Focusing on this helps to justify it from the skepticism of experimental philosophers who follow Weinberg, Nichols & Stich (2001). To explore the experimental aspect of philosophical conceptual analysis, I consider a simpler instance of the same activity: everyday linguistic interpretation. I argue that this, too, is experimental in nature. And in both conceptual analysis and linguistic interpretation, the intuitions considered problematic by experimental philosophers are necessary but epistemically irrelevant. They are like variables introduced into mathematical proofs which drop out before the solution. Or better, they are like the hypotheses that drive science, which do not themselves need to be true. In other words, it does not matter whether or not intuitions are accurate as descriptions of the natural kinds that undergird philosophical concepts; the aims of conceptual analysis can still be met.
2014. “Cognitive Science and Thought Experiments: A Refutation of Paul Thagard’s Skepticism.” Perspectives on Science 22: 98-121.
Paul Thagard has recently argued that thought experiments are dangerous and misleading when we try to use them as evidence for claims. This paper refutes his skepticism. Building on Thagard’s own work in cognitive science, I suggest that Thagard has much that is positive to say about how thought experiments work. My last section presents some new directions for research on the intersection between thought experiments and cognitive science.
2014. “On the Origins of the Philosophy of Thought Experiments: The Forerun.” Perspectives on Science 22: 13-54 (with Y. Fehige).
The history of thought experiments is now gaining a great deal of attention, and this is due to the renewed interest of philosophers on the subject. This paper inquires into the history of the philosophy of thought experiments. We name the period to be examined in this paper the “forerun.” Its main stakeholders are Georg C. Lichtenberg, Novalis, and Immanuel Kant. We will present and discuss the work of each of them in order to characterize the period, and then reveal parallels and lessons that apply to more recently proposed accounts of thought experiments.
2014. “Introduction to the Special Issue on Thought Experiments.” Perspectives on Science 22: 1-12 (with Y. Fehige).
This is the introduction to a special issue of Perspectives on Science, which was the outcome of a workshop entitled, “Thought Experiments in Science: Four Blind Spots,” held at the University of Toronto, March 23rd, 2012. The recent revival in philosophical study of thought experiments has mostly been limited to fields like epistemology, science studies, and metaphilosophy. With this issue we hope to facilitate a discussion about how some other disciplinary perspectives might bear on the subject; specifically, the history of philosophy, literary studies, phenomenology and cognitive science.
Forthcoming. Thought Experiments in the History of Philosophy of Science. HOPOS special issue (with Y. Fehige).
2018. The Routledge Companion to Thought Experiments. London: Routledge (with Y. Fehige and James R. Brown).
Thought experiments are a means of imaginative reasoning that lie at the heart of philosophy, from the pre-Socratics to the modern era, and they also play central roles in a range of fields, from physics to politics. The Routledge Companion to Thought Experiments is an invaluable guide and reference source to this multifaceted subject. Comprising over 30 chapters by a team of international contributors, the Companion covers the following important areas: the history of thought experiments, from antiquity to the trolley problem and quantum non-locality; thought experiments in the humanities, arts, and sciences, including ethics, physics, theology, biology, mathematics, economics, and politics; theories about the nature of thought experiments; new discussions concerning the impact of experimental philosophy, cross-cultural comparison studies, metaphilosophy, computer simulations, idealization, dialectics, cognitive science, the artistic nature of thought experiments, and metaphysical issues.
This broad ranging Companion goes backwards through history and sideways across disciplines. It also engages with philosophical perspectives from empiricism, rationalism, naturalism, skepticism, pluralism, contextualism, and neo-Kantianism to phenomenology. This volume will be valuable for anyone studying the methods of philosophy or any discipline that employs thought experiments, as well as anyone interested in the power and limits of the mind.
2014. Thought Experiments. Perspectives on Science special issue 22:2 (with Y. Fehige).
Forthcoming. “Thought Experiments.” Oxford Bibliographies (with J. R. Brown).
Forthcoming. “Thought Experiments.” The Palgrave Encyclopedia of the Possible.
2013. “Thought Experiments in Methodological and Historical Contexts edited by Katerina Ierodiakonou and Sophie Roux.” HOPOS: The Journal of the International Society for the History of Philosophy of Science 3: 154-57 (with J. Brown).
2012. “Laboratory of the Mind by James R. Brown.” Spontaneous Generations: A Journal for the History and Philosophy of Science 6: 237-241.
Forthcoming. “How Does Experimental Philosophy Fare under the P-Curve?” Post for the New Experimental Philosophy Blog. A blog on experimental philosophy managed by members of the University of Waikato Experimental Philosophy Group and the Australasian Experimental Philosophy Group.
Forthcoming. Post for Auxiliary Hypotheses, a blog by the British Society for the Philosophy of Science.
2019. “Ethics of Scientific Imagination: Who Gets to Use Imagination in Science?” Post for The Junkyard of the Mind, an academic blog on the imagination curated by Amy Kind of Claremont McKenna College.
2018. “From Painting to Pig-Human Hybrids: Imagination and Our Interaction with Art and Science.” The Junkyard of the Mind, an academic blog on the imagination curated by Amy Kind of Claremont McKenna College.
2017. “Using Imagination to Empathize with Space Robots, Demons, and Other Weird Stuff.” The Junkyard of the Mind, an academic blog on the imagination curated by Amy Kind of Claremont McKenna College.
2015. “Better Science Policy in Canada.” The Bubble Chamber, a blog on the history and philosophy of science.
MANUSCRIPTS (AVAILABLE ON REQUEST)
In Preparation “The Pragmatics of Scientific Representation: An In Vivo Study of Scientific Modelling”
In Preparation “Are there Thought Experiments in Chemistry, and if not, Why not?”
In Preparation “Empirically Disambiguating Imagination and Supposition” (with M. Kneer)