Oh gosh if I can tackle my probability demon once and for all and be able to stand firm on _something_ with it, I’ll be glad. Crossing between Mlodinow, Burton’s “On Being Certain: Believing You Are Right Even When You’re Not” with a smattering of Massimo Pigliucci, sure feels close. I feel as if I need to inject a little _something_ else but not sure yet. So I’ll explore in this direction for further narrowing:
“what are some hybrid concepts of probability and belief?”
Hybrid concepts of probability and belief can be found at the intersection of various disciplines, such as psychology, philosophy, decision-making, and even finance. Some of these hybrid concepts include:
Bayesian reasoning: A probabilistic approach to updating beliefs based on new evidence, using Bayes’ theorem. This method combines prior beliefs with new information to arrive at updated probabilities.
Subjective probability: The idea that individuals have personal probabilities or degrees of belief for specific events or hypotheses. These beliefs are influenced by personal experiences, cognitive biases, and emotions.
Belief revision: A field in philosophical logic that explores how to rationally update beliefs when confronted with new information, particularly when the new information contradicts previous beliefs.
Signal detection theory: A psychological framework for understanding decision-making under uncertainty, which considers the balance between correct and incorrect detections of a signal amidst noise.
Expected utility theory: A decision-making theory in economics and finance that combines probabilities with individual preferences to calculate the expected utility of various outcomes, helping to guide rational choices.
Confirmation bias: The psychological tendency to seek, interpret, and remember information that confirms one’s pre-existing beliefs while ignoring or discounting contradictory evidence.
The availability heuristic: A cognitive bias where people overestimate the probability of events that are more readily available in their memory, often due to recent exposure or emotional impact.
The representativeness heuristic: A cognitive bias where people judge the probability of an event based on how similar it is to a stereotype or a representative example, often leading to errors in probability estimation.
These hybrid concepts highlight the complex interplay between probability and belief, demonstrating how our understanding of uncertainty, decision-making, and rationality is shaped by both mathematical principles and human psychology.