The Causal Inference Lab hosts a number of funded research projects. The projects of current members of the Causal Inference Lab are listed below.
The topic of this project is the development and study of epistemic/doxastic dynamic logical systems that are able to deal with causal reasoning and their dynamics. We are aiming at building a bridge between work done on epistemic logic on the one hand (including the work by Baltag and Smets on logical systems that have a semantics for conditional belief) and and the work on causal models on the other hand (including the work by Halpern and Pearl that have a semantics for counterfactuals based on causal intervention and structural equations). The bridge will also allow us to use the newly developed formal systems to address puzzles such as the epistemic reading of counterfactual conditionals.
Foundations of Human Mechanistic Reasoning
This project aims for a better grasp of mechanisms. The concept of mechanisms is of historical and philosophical significance, promising to illuminate how humans reason with causation.
When we consider, say, that water quenches thirst, we do not calculate using statistics; rather, we imagine some bodily mechanism producing that effect. But the dominant approach to causal reasoning today—that of causal networks—unsuitably understands causation as a form of statistical inference. Thankfully, a new wave of humanities research on mechanisms has the potential, developed in this project, to surpass causal networks' picture of causal reasoning.
By setting our causal reasoning with mechanisms on firmer foundations, the project elucidates the common principles of mechanistic thought, makes step towards greater scientific unity—and ultimately, furnishes a sharper view of just what kind of reasoners we humans are.
Funded by the UvA Interdisciplinary Doctorate Agreement, 2018-2022
This project uses an interdisciplinary approach to elucidate why and how humans perform causal reasoning. Humans have been shown to posit causal relationships, even in situations where this might not be the case (e.g. illusions of causality). On the other hand, various studies have shown that humans are very sensitive to the specificities of causal systems and hence that we are very capable causal reasoners.