Traditionally, philosophers have been skeptical that the imagination can justify beliefs about the actual world. After all, how could merely imagining something give you any reason to believe that it is true? However, within the past decade or so, a lively debate has emerged over whether the imagination can justify empirical belief and, if so, how. This paper provides a critical overview of the recent literature on the epistemology of imagination and points to avenues for future research.

Science and fiction seem to lie at opposite ends of the cognitive-epistemic spectrum. The former is typically seen as the study of hard, real-world facts in a rigorous manner. The latter is treated as an instrument of play and recreation, dealing in figments of the imagination. Initial appearances notwithstanding, several central features of scientific modeling in fact suggest a close connection with the imagination and recent philosophers have developed detailed accounts of models that treat them, in one way or another, (...) as akin to fictions. This chapter will critically discuss the fictions approach as an epistemology of scientific modeling. (shrink)

Historically left to the margins, the topics of imagination and creativity have gained prominence in philosophy of science, challenging the once dominant distinction between ‘context of discovery’ and ‘context of justification’. The aim of this chapter is to explore imagination and creativity starting from issues within contemporary philosophy of science, making connections to these topics in other domains along the way. It discusses the recent literature on the role of imagination in models and thought experiments, and their comparison with fictions. (...) It then turns to the importance of constraints on imaginings in the scientific domain, as well as whether constraints can hinder creativity. The second part of the paper focuses on the social dimensions of science. It considers imagination and creativity of scientific communities, asks whether the institution of science promotes creativity (and whether we want it to) or if it encourages conservativeness, and ends with a reflection on the politics of imagination and creativity in science. (shrink)

Thought experiments, models, diagrams, computer simulations, and metaphors can all be understood as tools of the imagination. While these devices are usually treated separately in philosophy of science, this paper provides a unified account according to which tools of the imagination are epistemically good insofar as they improve scientific imaginings. Improving scientific imagining is characterized in terms of epistemological consequences: more improvement means better consequences. A distinction is then drawn between tools being good in retrospect, at the time, and in (...) general. In retrospect, tools are evaluated straightforwardly in terms of the quality of their consequences. At the cutting edge, tools are evaluated positively insofar as there is reason to believe that using them will have good consequences. Lastly, tools can be generally good, insofar as their use encourages the development of epistemic virtues, which are good because they have good epistemic consequences. (shrink)

Michael T. Stuart (2021 and 2022) has proposed imagination as an intellectual dual‐process virtue, consisting of imagination1 (underwritten by cognitive Type 1 processing) and imagination2 (supported by Type 2 processing). This paper investigates the consequences of taking such an account seriously. It proposes that the dual‐process view of imagination allows us to incorporate recent insights from virtue epistemology, providing a fresh perspective on how imagination can be epistemically reliable. The argument centers on the distinction between General Reliability (GR) and Functional (...) System Reliability (FSR), for example in relation to Kengo Miyazono and Uko Tooming's (2023) argument for epistemic generativity. Furthermore, the paper claims that the dual‐process virtue account enables us to integrate a wide range of findings from the literature on epistemology and imagination. Moreover, it suggests a novel way to distinguish the virtues of creativity and imagination and presents a case for viewing imagination as a virtue rather than a skill. (shrink)

Thought experiments play a role in science and in some central parts of contemporary philosophy. They used to play a larger role in philosophy of science, but have been largely abandoned as part of the field’s “practice turn”. This chapter discusses possible roles for thought experimentation within a practice-oriented philosophy of science. Some of these roles are uncontroversial, such as exemplification and aiding discovery. A more controversial role is the reliance on thought experiments to justify philosophical claims. It is proposed (...) that if we adopt an underlying empiricist view of concepts, then thought experiments can be seen as affording us contact with scientific practice, despite their seemingly a priori character. The advantages and drawbacks of thought experiments are discussed via comparison with case studies, on the one, and simulations on the other hand. The chapter closes with some remarks on how to combine thought experiments with other methods. (shrink)

Many philosophers have recently defended the epistemic value of imagination. In this paper, we expand these discussions into the realm of virtue epistemology by proposing and defending a virtue-theoretic conception of imagination. On this account, the intellectual virtue of imagination is a character trait consisting of dispositions to engage skilfully in activities characteristic of imagining, with good judgement and from appropriate epistemic motivations. We argue that this approach helps to explain important connections between related, but distinct, intellectual virtues, including creativity (...) and empathy, and reveals avenues for future work on how best to develop intellectually virtuous imagination. (shrink)

Artificial intelligence (AI) and machine learning (ML) models have undoubtedly become useful tools in science. In general, scientists and ML developers are optimistic – perhaps rightfully so – about the potential that these models have in facilitating scientific progress. The philosophy of AI literature carries a different mood. The attention of philosophers remains on potential epistemological issues that stem from the so-called “black box” features of ML models. For instance, Eamon Duede (2023) argues that opacity in deep learning models (DLMs) (...) is epistemically problematic in the context of justification, though not in the context of discovery. -/- In this paper, I aim to show that a similar epistemological concern is echoed in the epistemology of imagination literature. It is traditionally held that, given its black box features, reliance on the imagination is epistemically problematic in the context of justification, though not in the context of discovery. The constraints-based approach to the imagination answers the epistemological concern by providing an account of how we can rely on the imagination in the context of justification by way of constraints. I argue by analogy that a similar approach can be applied to the opaque DLM case. Ultimately, my goal is to explore just how far this analogy extends, and whether a constraints-based approach to opaque DLMs can answer the epistemological concern surrounding their black box features in the context of justification. -/- (Note that this paper is IN PROGRESS and UNPUBLISHED). (shrink)