User:IssaRice/Belief propagation and cognitive biases: Difference between revisions

Revision as of 06:11, 3 September 2018

"Several cognitive biases can be seen as confusion between probabilities and likelihoods, most centrally base-rate neglect." [1]
- confusing p-values with Pr(null hypothesis | data) seems like another instance of this.
I think a polytree graph like $X\rightarrow Z\leftarrow Y$ can illuminate the halo effect/horn effect
Maybe https://en.wikipedia.org/wiki/Berkson%27s_paradox The page even says "The effect is related to the explaining away phenomenon in Bayesian networks."
Fundamental attribution error? The simplified DAG would look like: situational influence → observed action ← personality. And the evidence feeds into the "observed action" node, which propagates upwards to the "situational influence" and "personality" nodes. I think the bias is that the "personality" node gets updated too much. Can belief propagation give insight into this?
This one might be too simple, but the idea of screening off I think can be visualized in a Bayesian network. Not sure where the belief propagation would come in though... Related here are [2]/stereotyping.
Hindsight bias seems like an evidence node misfiring and causing updates in the graph?

@@ Line 1: / Line 1: @@
 * "Several cognitive biases can be seen as confusion between probabilities and likelihoods, most centrally base-rate neglect." [https://www.greaterwrong.com/posts/tp4rEtQqRshPavZsr/learn-bayes-nets]
+** confusing p-values with Pr(null hypothesis {{!}} data) seems like another instance of this.
 * I think a polytree graph like <math>X\rightarrow Z \leftarrow Y</math> can illuminate the halo effect/horn effect
 * Maybe https://en.wikipedia.org/wiki/Berkson%27s_paradox The page even says "The effect is related to the explaining away phenomenon in Bayesian networks."