belief

Our Stories

The stories we tell ourselves can be stubbornly resistant to change. Case in point: a recent story by Michael Lewis for This American Life.  

 "These stories we tell about ourselves-- they're almost like our infrastructure, like railroads or highways. We can build them almost any way we want to. But once they're in place, this whole inner landscape grows up around them. So maybe the point here is that you should be careful about how you tell your story, or at least conscious of it. Because once you've told it, once you've built the highway, it's just very hard to move it. Even if your story is about an angel who came out of nowhere and saved your life, even then, not even the angel herself can change it."  ~Michael Lewis

 

Beliefs

According to Andrew Newberg and Robert Waldman in Why We Believe What We Believe, we form our beliefs using four methods. First, we use evidence. We have first hand experience of something.

Second, we use logic. If this, then that.

Third, we use emotion. A strong emotional reaction creates an association.

Finally, we use society. Social expectation and/or belief, influences our beliefs.

What beliefs are you holding onto? Can you see how they might have been created?

Baye's Theorem

Baye's Theorem is named after an 18th-Century Presbyterian minister Thomas Bayes. The theorem tries to understand the probability of a belief or hypothesis in light of new evidence. The theory can be broken down like this: "In the face of uncertainty, a Bayesian asks three questions: How confident am I in the truth of my initial belief? On the assumption that my original belief is true, how confident am I that the new evidence is accurate? And whether or not my original belief is true, how confident am I that the new evidence is accurate?"

Honestly, it kind of feels like the Work of Byron Katie.

Now for the theorem: the posterior probability of a hypothesis is equal to the product of (a) the prior probability of the hypothesis and (b) the conditional probability of the evidence given the hypothesis, divided by (c) the probability of the new evidence.

Basically the theorem helps to answer the question of what does new evidence do to your prior belief? Mathematically, it often changes it. Philosophically - well, that's another matter.