Causality, regularity, and variation. A reassessment
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This document discusses causality theory and the role of regularity and variation in causal discovery. It argues that causal theory can be understood as a "mosaic" made up of different concepts that address scientific and philosophical questions about causality. Variation plays an important role in causal epistemology by allowing for diversity in methods while ensuring unity in causal theory. Regularities provide constraints on variations that are important for establishing generic causal relationships. Information may be a useful overarching concept for understanding causal production. The document advocates for a pluralistic but coordinated approach to causal theory.
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Causality, regularity, and variation. A reassessment
- 1. Causality, regularity, and variation. A reassessment Federica Russo Philosophy | Humanities | Amsterdam russofederica.wordpress.com | @federicarusso
- 2. Overview The mosaic of causal theory Fragmentation and unification of causal theory Regularity and variation in causal discovery 2
- 3. THE MOSAIC OF CAUSAL THEORY 3
- 4. An inventory … necessary and sufficient; levels; evidence; probabilistic causality; counterfactuals; manipulation and invariance; processes; mechanisms; information exogeneity; Simpson’s paradox; dispositions; regularity; variation; action; inference; validity; truth; … 4
- 5. Philosophical Questions Metaphysics What is causality? What kind of things are causes and effects? Semantics What does it mean that C causes E? Epistemology What notions guide causal reasoning? How can we use C to explain E? Methodology How to establish whether C causes E? Or how much of C causes E? Use What to do once we know that C causes E? Scientific Problems Inference Does C cause E? To what extent? Prediction What to expect if C does (not) cause E? Explanation How does C cause or prevent E? Control What factors to hold fixed to study the relation between C and E? Reasoning What considerations about whether / how / to what extent C causes E? 5
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- 7. Tiles for the Causal Mosaic … necessary and sufficient; levels; evidence; probabilistic causality; counterfactuals; manipulation and invariance; processes; mechanisms; information exogeneity; Simpson’s paradox; dispositions; regularity; variation; action; inference; validity; truth; … To be arranged by Philosophical Questions Metaphysics, Semantics, Epistemology, Methodology, Use Scientific Problems Inference, Prediction, Explanation, Control, Reasoning 7
- 8. A causal mosaic A picture made of tiles Each tile has a role that Is determined by the scientific problem / philosophical question it addresses Stands in a relation with neighbouring concepts A causal mosaic is dynamic, partly depends on scientists’ / philosophers’ perspectives 8
- 9. FRAGMENTATION AND UNIFICATION OF CAUSAL THEORY 9
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- 12. REGULARITY AND VARIATION IN CAUSAL DISCOVERY 12
- 13. A methodological mess? Causal methods in different disciplines Social science, epidemiology, experimental physics, molecular biology, econometrics, ethnography, political science, … Different types of causal methods Experimental, observational, quasi-experimental, in silico, … 13
- 14. An overarching question How to establish that C causes E? Epistemological reading: What notion guides our reasoning in model building and model testing? 14
- 15. Philosophical Questions Metaphysics What is causality? What kind of things are causes and effects? Semantics What does it mean that C causes E? Epistemology What notions guide causal reasoning? How can we use C to explain E? Methodology How to establish whether C causes E? Or how much of C causes E? Use What to do once we know that C causes E? Scientific Problems Inference Does C cause E? To what extent? Prediction What to expect if C does (not) cause E? Explanation How does C cause or prevent E? Control What factors to hold fixed to study the relation between C and E? Reasoning What considerations about whether / how / to what extent C causes E? 15
- 16. How to answer that question? Examine: Scientific practice Practice of causal methods Philosophical methodology Engage with the practice, raise philosophical questions, back to the practice, again to philosophy, … Philosophy of Science in Practice, Causality in the Sciences, Philosophy of Information, … 16
- 17. The Humean precept Thou shalt observe effects regularly following their causes Thou shalt find the constant conjunction 17
- 18. A Millian approach Agreement: compare different instances in which the phenomenon occurs. Difference: compare instances in which the phenomenon does occur with similar instances in which it does not. Residues: subdue from any given phenomenon all the portions which can be assigned to known causes, the remainder will be the effect of the antecedents which had been overlooked or of which the effect was as yet an un-known quantity. Concomitant Variation: examine presence of permanent causes or indestructible natural agents, impossible either to exclude or to isolate, and that we cannot control. Compare concomitant variations to detect the causes. J.S. Mill, System of Logic The experimental method is based on the Baconian rule of varying the circumstances The Four Methods are all based on the evaluation of variations 18
- 19. A modified Geirean approach Does smoking causes lung cancer? Compare two hypothetical populations 1. Everyone smokes 2. Nobody smokes Lung cancer rates must be higher in 1 than in 2 No variation, no causation One real population Some smoke a lot, some a little, some don’t Some get lung cancer, some don’t Detect some joint variation between C and E Epistemological point, mirrored into methodology 19
- 20. Variational epistemology and methodology Causal discovery (experiments, statistics) Search for differences Probability of the outcome given the cause; effects of manipulations; … Causal explanation Most causes are ‘difference-makers’ in mechanisms regulating phenomena (e.g. health and behaviour) 20
- 21. The role of regularity Statistical regularity Causal methodology needs regularity as a constraint on variations, differences Regular causal relations are ‘generic’ Population-level, repeatable Hence we need regularity to establish generic level 21
- 23. Use Epistemology Methodology Metaphysics Semantics 23 Establish that C causes E Difference-making Establish how C causes E Production
- 24. Use Epistemology Methodology Metaphysics Semantics 24 Establish that C causes E Difference-Making Variation: the most general notion of difference-making ➢ Preserving diversity of methods, while ensuring unity of causal theory ➢ Against gold standards, for comparable methods
- 25. Use Epistemology Methodology Metaphysics Semantics Establish how C causes E Production Information: the most general notion of causal production ➢ Helps address: - Problem of omissions - Inhomogeneity of causal factors ➢ Compatible with mechanisms and processes
- 26. TO SUM UP AND CONCLUDE 26
- 27. Causality A traditional, thriving, and timely topic Scientific practice, philosophical thinking Abundance of notions, concepts, approaches A sign of its complexity Possible responses to the myriad of notions, concepts, approaches Staunch monism, ad hoc pluralism OR: Mosaic 27
- 28. Regularity–Variation reassessment A tile A tile in a mosaic Variation Gives unity to causal epistemology while allowing for methodological diversity Does not compete with regularity, it gives it a different role 28
- 29. The causal mosaic as a philosophical enterprise Not ‘anything goes’ Timely philosophy Science in practice, conceptual design Collaborative No counterexample factory, Distributed philosophical achievement 29
- 30. Further readings P. Illari and F. Russo, Causality: Philosophical Theory Meets Scientific Practice, OUP 2014 F. Russo, Causality and Causal Modelling in the Social Sciences. Measuring Variations, Springer 2009 P. Illari and F. Russo, ‘Causality and information’, in The Routledge Handbook of Philosophy of Information, 2016 P. Illari and F. Russo, ‘Information channels and biomarkers of disease’, Topoi 2014 L. Floridi, ‘What is a philosophical question?’, Metaphilosophy 2013 L. Floridi, ‘A defence of constructionism: philosophy as conceptual engineering’, Metaphilosophy, 2011 30
Notas del editor
- The sciences, ranging from the biomedical to the social and to physical sciences, deploy a variety of methods to unveil causal relations and to model phenomena. In this talk, I will argue that the common denominator of causal reasoning in different scientific domains is the notion of variation. The point is epistemological in character. I will be focusing on how we reason about cause-effect relationships, namely about what it is that we ‘look for’ and put forward for further testing and evaluation. I shall argue that causality needs difference, or variations, because in a situation of indifferentiation we would not be able to perceive, or recognise, the presence of causes. Since Hume, we are acquainted to associate causality with regularity. I contend that even when we try to find causal explanation for regularities, it is via difference and variation that we reason. In this sense, the notion of variation is what grounds causal reasoning across different methods of scientific enquiry.
- Giere’s book: Understanding scientific reasoning