Scientific Imagination

The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Questionable research practices such as p-hacking are thought to inflate Type I error rates above their nominal level, leading to unexpectedly high levels of false positives in the literature and, consequently, unexpectedly low replication rates. In this article, I offer an alternative view. I argue that questionable and other research practices do not usually inflate relevant Type I error rates. I begin (...) with an introduction to Type I error rates that distinguishes them from theoretical errors. I then illustrate my argument with respect to model misspecification, multiple testing, selective inference, forking paths, exploratory analyses, p-hacking, optional stopping, double dipping, and HARKing. In each case, I demonstrate that relevant Type I error rates are not usually inflated above their nominal level, and in the rare cases that they are, the inflation is easily identified and resolved. I conclude that the replication crisis may be explained, at least in part, by researchers’ misinterpretation of statistical errors and their underestimation of theoretical errors. (shrink)

Scientists imagine for epistemic reasons, and these imaginings can be better or worse. But what does it mean for an imagining to be epistemically better or worse? There are at least three metaepistemological frameworks that present different answers to this question: epistemological consequentialism, deontic epistemology, and virtue epistemology. This paper presents empirical evidence that scientists adopt each of these different epistemic frameworks with respect to imagination, but argues that the way they do this is best explained if scientists are fundamentally (...) epistemic consequentialists about imagination. (shrink)

There is a tendency to take mounted dinosaur skeletons at face value, as the raw data on which the science of paleontology is founded. But the truth is that mounted dinosaur skeletons are substantially intention-dependent—they are artifacts. More importantly, I argue, they are also substantially imagination-dependent: their production is substantially causally reliant on preparators’ creative imaginations, and their proper reception is predicated on audiences’ recreative imaginations. My main goal here is to show that dinosaur skeletal mounts are plausible candidates for (...) art-status. But, what is more, I think they are artworks—specifically, sculptures. (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)

Artificial intelligence (AI) technologies are used in various domains of human activities, and one of these domains is scientific research. Now, researchers in many scientific areas try to apply AI technologies to their research and automate it. These researchers claim that the ‘automation of science’ will liberate people from non-creative tasks in scientific research, and radically change the overall state of science and technology so that large-scale innovation results. As I see it, the automation of science is remarkable in another (...) respect: since science is one of the most distinctive human activities, the tendency of automating it prompts us to reconsider the aspects of our humanity itself. One of these aspects is concerned with human creativity, on which this article focuses. In this article, I address two questions concerning the automation of science: first, ‘Can AI makes creative discovery?’; second, ‘What implications may the automation of science have on science and society?’. Scientific discovery is said to be one of the most creative phases of scientific research. I show that, though there are no reasons in principle why AI could not make creative discovery, we do not at present have enough knowledge how to realize it. If the automation of science nevertheless proceeds, the cultural values science as a creative activity has might be reduced, and it might alter the state of scientific community and its relationship with society in some undesirable way. Therefore, I conclude, we need to specify desirable ways of introducing AI technologies into science and devise measures against demerits of automating science. (shrink)

Anti-cognitivism is best understood as a challenge to explain how works of fictional narrative can add to our worldly knowledge. One way to respond to this challenge is to argue that works of fictional narrative add to our knowledge by inviting us to explore, in the imagination, the perspectives or points of view of others. In the present paper, I distinguish two readings of this thesis that reflect two very different conceptions of “perspective”: a first understanding focuses on what the (...) world looks like from a subjective point of view. Within this framework, we can distinguish approaches that focus on the subjective character of experience from others that explore the nature of subjectivity. I will argue that both strands can be successful only if they acknowledge the de se character of imagining. The second conception understands perspective as a method of representing. To illustrate it, I will look back to the invention of linear perspective in Renaissance painting. I will argue that the definition of perspective as a rule-guided method or technique can shed new light on the thesis that works of narrative fiction are particularly suited to display other perspectives. (shrink)

The current debate on literary cognitivism in the philosophy of fiction typically assumes that we can rigorously distinguish between fictional and factual, and focuses on the question of whether and how works of fiction can impart propositional knowledge to the reader. In this paper we suggest that this way of framing the debate may be problematic. We argue that works of fiction almost inevitably include a reference to the real world and that – contrary to what is usually assumed – (...) the exchange between fiction and reality is vivid as well as potentially fruitful. We shed a new light on these complex dynamics by building on the metaphors of trade exchange and smuggling between the two worlds. While the current debate exclusively focuses on cognitively relevant goods that “officially” cross the border through “customs”, as it were, we show that exchanges between fiction and reality run deeper. Indeed, as we show, a substantial part of the cognitive impact that we derive from fiction goes “under the table” and is “smuggled” from fiction to reality. As such, it bypasses the audience’s conscious control, which in turn explains the manipulative force that fiction can exert. Smuggling takes place when cognitively relevant contents are passed on to the reader in subliminal ways, as it happens when they imprint implicit biases or prejudices, shift perspectives or subtly modify habits or patterns of behavior. By elaborating on the metaphors of trade exchange and smuggling, we aim at presenting a more comprehensive and nuanced understanding of the relations between fiction and reality and on the impact that imagination has on our real-world beliefs. (shrink)

Sometimes, scientific models are either intended to or plausibly interpreted as representing nonactual but possible targets. Call this “hypothetical modeling”. This paper raises two epistemological challenges concerning hypothetical modeling. To begin with, I observe that given common philosophical assumptions about the scope of objective possibility, hypothetical models are fallible with respect to what is objectively possible. There is thus a need to distinguish between accurate and inaccurate hypothetical modeling. The first epistemological challenge is that no account of the epistemology of (...) hypothetical models seems to cohere with the most characteristic function of scientific modeling in general, i.e., surrogative representation. The second epistemological challenge is a version of “reliability challenges” familiar from other areas. There is a challenge to explain how hypothetical models could be a reliable guide to what is possible, given that they are not and cannot be compared against their nonactual targets and updated accordingly. I close with some brief remarks on possible solutions to these challenges. (shrink)

Is there a role for aesthetic judgements in science? One aspect of scientific practice, the use of thought experiments, has a clear aesthetic dimension. Thought experiments are creatively produced artefacts that are designed to engage the imagination. Comparisons have been made between scientific (and philosophical) thought experiments and other aesthetically appreciated objects. In particular, thought experiments are said to share qualities with literary fiction as they invite us to imagine a fictional scenario and often have a narrative form (Elgin 2014). (...) But philosophical discussions of aesthetics in science have focused mainly on the epistemic role of beauty and elegance when it comes to theories and mathematical proofs, and thought experiments have been widely overlooked. My aim in this chapter is to address how the aesthetic choices scientists make in the design of a thought experiment contribute to its function: to communicate, convince, or explain a theory or phenomenon. A key issue is whether any aesthetic features in science provide anything beyond catching our attention, or are at best, a mere heuristic aid. I respond to accounts that argue this way and show how formulation is important in scientific thought experiments and, similarly to literary fictions, there is more than one way of interpreting a thought experiment scenario. I end by considering which literary examples are most appropriate when making comparisons with thought experiments. As a result, the difference between representations in art and science raised in current discussions is not as stark as it has been made out to be, and science is a more heterogeneous practice than has been allowed. Part of the value of thought experiments in scientific practice includes the qualities they share with literary works. (shrink)

Theoretical models are widely held as sources of knowledge of reality. Imagination is vital to their development and to the generation of plausible hypotheses about reality. But how can imagination, which is typically held to be completely free, effectively instruct us about reality? In this paper I argue that the key to answering this question is in constrained uses of imagination. More specifically, I identify make-believe as the right notion of imagination at work in modelling. I propose the first overarching (...) taxonomy of types of constraints on scientific imagination that enables knowledge of reality. And I identify two main kinds of knowledge enabled by models, knowledge of the imaginary scenario specified by models and knowledge of reality. (shrink)

When introduced around 1925, interdisciplinarity, grounded in the notion of the unity of knowledge, was meant to reconnect the fragmented and specialized disciplines of academia. However, interdisciplinary research became more and more challenging as the plurality and heterogeneity of disciplinary perspectives and insights increased. Insisting on this divergence and diversity, Julie Thompson Klein has nonetheless contributed in important ways to convergence in interdisciplinarity with her work on the process of integration as interdisciplinarity's defining feature. Of course, she is aware that (...) the increasing inclusion of extra-academic stakeholders in transdisciplinary research constitutes a fundamental challenge to integrative interdisciplinarity. This challenge implies that next to academic contributions, experiential knowledge, interests, and norms must be recognized as valuable to the process, and stakeholder expectations of applicable results must be met. Exploring the future by extending this crucial development further, this article focuses on the actionability of knowledge as an additional criterion for effective interdisciplinarity and transdisciplinarity, as it is in Action Research. With action options for stakeholders being an important goal for such research, it is argued that joint deliberation about these options must be part of the process, aiming for reflective equilibrium. At the same time, an important role for imagination is defended, enabling adequate consideration of action options with their ramifications and implications. The future of interdisciplinarity, it is concluded, will entail an important role for the actionability criterion and for the related role of imagination of potential outcomes, much greater roles than these now have. (shrink)

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. (shrink)

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. (shrink)

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 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. (shrink)

Theology, philosophy, and science have been in mutual conversation for centuries, but the major debates have nearly always dealt with explanations rather than ways of living. Over and above explanatory or theoretical issues, there are other boundary issues that can be called practical. These are often neglected because they do not deal with what scientists or theologians say. They deal rather with what scientists and theologians do. As recent work in the history of the natural sciences shows, it is a (...) mistake to see scientific theories as timeless entities totally detached from the philosophical, theological, and cultural environments in which they are born. A cultural paradigm affects, and is in turn affected by, the discovery and formulation of any given major theory. Moreover, cultural paradigms affect individuals not only in their thinking but also in their living. This paper explores the neglected dimension of how the conversation between theology, philosophy, and the natural sciences impacts on existential concerns. I will do this by first determining two key areas of this practical dimension, and then, in section two, by considering and eventually blocking some objections. I will conclude by drawing some concrete proposals on how to take this discussion further. (shrink)

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.

History indicates that science is primarily not a theoretical but a practical enterprise. It represents the symbiosis of two human activities, namely, on the one hand, natural philosophy, which seeks to make sense of the world, and, on the other hand, instrumental thinking, which seeks to control the world.

Are science and religion completely independent of each other? Can scientists work exclusively in the scientific domain without being influenced in any way by their own religious or other commitments? These questions have been treated in a number of ways in the course of history. In recent decades, advances in physics and biology have raised new possibilities for a deeper understanding of the issue and for a clearer picture of the right kind of interaction between science, religion, and moral values.

In this paper, I will analyze Rawad El Skaf’s (2017 & 2021) account of thought experiments (TEs) in physics. I will argue that El Skaf’s account is strengthened by taking on Amy Kind’s (2016 & 2018) constraints-based approach to the imagination, which highlights the epistemic significance of imaginative processes. First, I will present El Skaf’s step-by-step structure of TEs wherein he discusses their form, content, and epistemic function. Second, I will explain a canonical TE in physics known as the clock-in-the-box. (...) In turn, I will lay out El Skaf’s analysis of the clock-in-the-box TE. Then, I will present Amy Kind’s constraints-based approach to the imagination. I will then offer three critiques of El Skaf’s account and suggest that each critique is resolved by applying a constraints-based approach to his view. Once the hybrid view is laid out, I will discuss incompatible constraints on the imagination, which I call the home and away constraints. I will argue that a thought experimenter (TEer) may overcome this incompatibility by transforming away constraints into home constraints via metaphor. Lastly, I will argue that physics TEs are special since it is an essential feature of theirs that they ask the TEer to consider incompatible constraints on the imagination. (shrink)