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.
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;
…
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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?
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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
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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, …
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14. An overarching question
How to establish that C causes E?
Epistemological reading:
What notion guides our reasoning in model building
and model testing?
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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?
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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, …
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17. The Humean precept
Thou shalt observe effects regularly following
their causes
Thou shalt find the constant conjunction
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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
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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
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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)
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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
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24. Use
Epistemology
Methodology Metaphysics
Semantics
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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
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
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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
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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
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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
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Editor's Notes
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.