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Public Lecture:
Causation Science and Everyday Life
Date: 28 September 2026 (Mon)
Time: 4:30pm-6:30pm
Venue: Cho Yiu Hall
Abstract:
Causation is a concept that plays a central role in the sciences, in law, in ethics, and in everyday life. Philosophers have been trying to offer analyses of the concept of causation for hundreds of years. In this talk, I want to highlight a particular challenge for this project. One the one hand, we investigate causal relationships using scientific methods—controlled experiments, mathematical modeling, statistical analysis, etc.—and incorporate them into our scientific image of the world. On the other hand, empirical evidence from psychology shows that when people make causal judgments, they are influenced by things like expectations, moral values, social rules, actors’ intentions, and other subjective and pragmatic factors. This raises the question of how one concept can answer to both descriptions: How can it be an objective part of the world described by science and also dependent on norms and expectations? I resolve this tension by showing how ordinary causal ascriptions serve a function such as an executive summary or an index (such as the consumer price index).
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Departmental Seminar:
Causal Models for Philosophy
Date: 12 October 2026 (Mon)
Time: 4:30pm-6:30pm
Venue: Room 220, Fung King Hey Building
Abstract:
Philosophers have adopted a variety of formal tools for use in philosophical projects. The early twentieth century saw philosophers turn to the new field of mathematical logic to address fundamental questions in philosophy; in the middle of the twentieth century many philosophers began to make use of probability theory; later in the twentieth century, decision theory found its way into philosophical theorizing. I will make a case for adding causal models, particularly structural equation models and graphical causal models, to the philosophers’ tool kit. It has been widely noted that causation is an ingredient in many concepts of interest to philosophers, which has often been used to motivate traditional “analyses” of causation. I will argue that causal models are often more useful tools than traditional analyses for shedding light on these philosophical concepts. I will support this claim with two illustrations: the Doctrine of Double Effect in ethics, and the propensity interpretation of probability. *
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