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Wolff, P. (2007). Representing causation. Journal of experimental psychology: General, 136(1), 82.
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Anything goes!
From a pluralism of methods towards a unified theory of causal cognition
Lara Kirfel and Tobias Gerstenberg
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Commentary
David Danks
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Kirfel, L., Icard, T., & Gerstenberg, T. (2022). Inference from explanation. Journal of Experimental Psychology: General, 151(7), 1481–1501.
The use of diverse methods in research on causal cognition has come with a plurality of theories about how causal cognition works. However, causal pluralism in psychology and philosophy might be unsatisfactory for various reasons. Where does this leave us as experimental researchers and philosophers engaging with empirical research? In this symposium, Lara Kirfel and Tobias Gerstenberg (Stanford University) argue that we should hold on to a plurality of methods, with David Danks (UCSD) providing commentary.
Bechlivanidis, C., Schlottmann, A., & Lagnado, D. A. (2019). Causation without realism. Journal of Experimental Psychology: General, 148(5), 785.
Woodward, J. (2007). Interventionist theories of causation in psychological perspective. Causal learning: Psychology, philosophy, and computation, 19-36.
Pearl, J. (2000). Causal inference without counterfactuals. Journal of the American Statistical Association, 95(450), 428-431.
Gerstenberg, T., Goodman, N. D., Lagnado, D. A., & Tenenbaum, J. B. (2021). A counterfactual simulation model of causal judgments for physical events. Psychological Review, 128(6), 936-975.
“If we want to understand nature, if we want to master our physical surroundings, then we must use all ideas, allmethods, and not just a small selection of them.”References
Leyssen, S. 2021. “Remaking ‘Michotte’: Reusing and Remaking Moving Images in the History of Perception Research.” Isis 112 (2): 315–25.
To study causal perception, psychologists nowadays use computer-generated animations of object collisions (see Figure 1b). In studying under which conditions people perceive causality in the interactions of objects, Michotte not only invented a new experimental paradigm. Research on causal perception has also informed the philosophical question of what causality is. Process theories of causation (Michotte, 1946; Salmon, 1994; Wolff 2007) postulate that there must be a spatiotemporally continuous process (such as a transfer of force) between two objects in order for them to be conceptualized as cause and effect.
Kirfel & Gerstenberg advance two main theses in response to this fragmentation. First, they argue that we psychologists and philosophers should use every available method to understand causal cognition. Researchers have increasingly used diverse methods in this field, but as they argue, we all can do better. Understanding causal cognition is a classic “hard problem,” and so we will undoubtedly need to use every available resource if we hope to make progress on it. At the same time, we will also need research on the different types of information provided by different methods, and the constraints that they imply on each other. The type of methodological pluralism advocated by Kirfel & Gerstenberg presupposes that we will eventually be able to combine the results—data, empirical phenomena, and so forth—revealed by the different methods. But such integration will require (substantial) additional research on our psychological and philosophical methods. If we want to avoid further fragmentation from “Anything goes!” in terms of our techniques and methods, then we need to study not only causal cognition, but also those methods themselves.
How, then, should we leverage psychology’s broad methodological spectrum in order to probe a unified causal concept? As practitioners working at the intersection of philosophical theory and empirical research, we agree with Dinh and Danks that it is desirable to hold onto a unified view of causation in human cognition. Moreover, we argue that as psychologists and philosophers, we should employ a pluralism of methods precisely because we are interested in a unitary theory of causal cognition. However, we want to make an alternative proposal about what kind of unified picture of causal cognition we should strive for. While most research in the empirical sciences has focused on uncovering how causal cognition works, less attention has been paid to the question of what causal cognition is for (Woodward, 2021). And while it might be the case that causal cognition draws on a diversity of cognitive processes, it is yet an open question what function it actually serves. On the one hand, the answer to this question might appear obvious, especially when we consider people’s ability to grasp general causal relationships. Understanding general causal relationships enables us to make predictions about the future, inferences about the past, and allows us to choose actions that suit our goals. One the other hand, what function the practice of making causal judgments about particular events plays is less clear. Why do we judge that one cause contributed to an outcome more so than another? Why do we select certain causes in our explanations of events, and dismiss others? Crucially, neither process nor dependence theories fully answer the question of what purpose causal judgments serve.
An open question about this second thesis is whether the output of the functionalist approach should be understood as a means to develop other types of theories (e.g., by identifying constraints on mechanistic or rationalist models), or rather as an end in itself (e.g., a theory that need not be connected in any significant way with mechanistic accounts). Put somewhat differently, are Kirfel & Gerstenberg arguing that we should aim to develop functional analyses of causation and causal cognition, or provide functional definitions of them? The former would ideally connect with other theories about causal cognition, while the latter would not necessarily do so. If we adopt “Anything goes!” in terms of our approach, then are we giving up on the goal of a unified account of causal cognition?
Michotte, A. (1946). The perception of causality, trans. R. Miles and E. Miles (London: Methuen & Co., Ltd., 1963).
Albert Michotte, a Belgian experimental psychologist working in the post world war era, was one of the first psychologists to study causal cognition. To do so, Michotte invented his own experimental machinery, the “Banc Michotte” (see Figure 1a). In a sophisticated set up consisting of rotating discs with coloured lines, this machine created a visual illusion of moving and interacting physical objects. With the help of this machine, Michotte discovered the famous “launching effect”: if one object stops before another and the other object starts to move directly after, people perceive the first object to have caused the other one to move.
Rottman, B. M., & Keil, F. C. (2012). Causal structure learning over time: Observations and interventions. Cognitive psychology, 64(1-2), 93-125.
Woodward, J. (2021). Causation with a human face: Normative theory and descriptive psychology. Oxford University Press.
One might also worry about the odds of success for a functional approach. In general, functionalist approaches work best when their target—causal cognition in this case—has only a small number of functions, ideally only one. If the target cognition could serve many different functions depending on context, goals, stimuli, and so forth, then our functionalist analysis can readily fragment into too many different pieces to be scientifically or philosophically useful. Kirfel & Gerstenberg consistently talk in the singular about the function or purpose, thereby implying that causal cognition (or at least, causal judgments about particular events) has a univocal function. But as they show, many different factors have been shown to impact causal judgments depending on the context, pragmatic needs, shared background knowledge, and much more. These empirical results suggest that causal judgments might serve multiple functions, depending on those contexts, needs, knowledge, and so forth. A functionalist approach to causal cognition might lead to insights, but we need to be careful not to focus on just one of the many plausible functions.
Dinh, P. P. N., & Danks, D. (2021). Causal pluralism in philosophy: Empirical challenges and alternative proposals. Philosophy of Science, 88(5), 761-772.
Welcome to the Brains Blog’s Symposium series on the Cognitive Science of Philosophy. The aim of the series is to examine the use of empirical methods to generate philosophical insights.
The second main thesis of Kirfel & Gerstenberg is likely more controversial: Research on causal cognition should include understanding the function of causal cognition, not just “what causation is (in the mind).” In general, functionalist accounts can highlight or reveal features that are otherwise neglected or hard-to-study. Moreover, they can provide substantial constraints on the cognitive processes and representations that (aim to) achieve the identified functions; there is no irreconcilable tension between functionalist and more mechanistic approaches to studying causal cognition. Kirfel & Gerstenberg argue specifically that we can make progress on understanding causal judgments about specific events by examining their function, particularly since it is not immediately obvious what that function might be.
Griffiths, T. L., & Tenenbaum, J. B. (2005). Structure and strength in causal induction. Cognitive psychology, 51(4), 334-384.
Kirfel & Gerstenberg persuasively argue for an “Anything goes!” expansion of the toolbox of methods, approaches, and theories that we use to study causal cognition. There has been substantial collective progress in this area, but we can (and should) do better as a community. At the same time, we should do so with our eyes open to the challenges of such an expansion. If we want to avoid the downside risk of further fragmentation, then we need to ensure that we have the knowledge and ability to integrate the results of different methods and approaches.
Lejarraga, T., & Hertwig, R. (2021). How experimental methods shaped views on human competence and rationality. Psychological Bulletin, 147(6), 535.
