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SUMMARY:Rational Belief Polarisation: A Bayesian Network Model of Bias Att
 ributions - David Young (University of Cambridge)
DTSTART:20230531T140000Z
DTEND:20230531T150000Z
UID:TALK200116@talks.cam.ac.uk
CONTACT:Edoardo Chidichimo
DESCRIPTION:It is common within politics for people to be accused of bias 
 – and not without good reason. Many political actors are willing to say 
 things they do not believe in order to push a particular agenda\, while ot
 hers are inadvertently biassed due to biases in their reasoning or the inf
 ormation they consume. This means many of the political information source
 s we encounter will make claims in support of particular parties\, policie
 s\, politicians and ideologies irrespective of whether they are actually t
 rue. Determining who is biassed\, how they are biassed\, and accounting fo
 r these biases\, is crucial to ascertaining political reality. Despite thi
 s\, bias has only recently begun to be studied as a source characteristic.
  I will present a Bayesian Network model of how people can infer and corre
 ct for source bias when attempting to learn political information. I will 
 also discuss an intriguing prediction of this model\, which is that people
  exposed to testimony from two sources who consistently disagree with each
  other should polarise. The model therefore provides a rational explanatio
 n of mass belief polarisation when people are exposed to the same informat
 ion. I present preliminary evidence that this model accurately predicts be
 lief updating\, and contributes to belief polarisation in both the lab and
  real world.\n
LOCATION:Ground Floor Lecture Theatre\, Department of Psychology\, Downing
  Site\, Cambridge
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