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SUMMARY:Two views on the relation between causality and probability - Dona
 ld Gillies (UCL)
DTSTART:20130515T120000Z
DTEND:20130515T133000Z
UID:TALK44962@talks.cam.ac.uk
CONTACT:Vashka dos Remedios
DESCRIPTION:The relation between causality and probability is a very compl
 icated matter whose discussion has generated many paradoxes and controvers
 ies. In short \nit is a philosophical minefield. In this paper\, I will co
 ncentrate on only one aspect of the problem\, namely the debates about the
  Markov\, or Screening-Off\, Condition. Reichenbach in 1956 proposed a cau
 sal model called a conjunctive fork\, which satisfied the Markov condition
 \, but later \nSalmon produced a causal model\, called an interactive fork
 \, which did not satisfy this condition. In the 1980s the theory of causal
  networks was developed in a striking fashion by Pearl and others. Pearl s
 pecified that every node in what he called a 'Bayesian network' had to sat
 isfy the Markov \ncondition. Yet the Markov condition was criticized in th
 e 1990s by Cartwright\, who maintained that the Markov condition is 'a ver
 y special case that holds in unusual circumstances'. In this paper\, I wil
 l analyse this controversy between Pearl and Cartwright\, and then go on t
 o consider the multi-causal forks\, which have become common in modern med
 icine. I will argue that such forks are best handled by a non-Markovian ca
 usal model. The \npaper is designed for anyone with general interests in p
 hilosophy of science rather than for specialists in causal modelling. So t
 echnical terms such as conjunctive fork\, interactive fork\, Markov condit
 ion\, Bayesian network\, multi-causal fork\, etc. will be fully explained 
 in the course of paper and illustrated by examples.
LOCATION:Seminar Room 2\, Department of History and Philosophy of Science
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