Probability can seem like a slippery notion. Indeed, though we have an intuitive notion of various aspects of probability, it took a long time for humanity to develop a rigorous formal theory. And even with the mathematics of probability on surer footing, the interpretation of probability -- what does it mean -- is still plagued… Continue reading Paper Review: Contribution to discussion on Probability
Can two rational people agree to disagree? This question seems really important to me. When having a conversation with a friend, for example, if we are both good-faith rational actors who are engaged in a collective truth-seeking endeavor (as is my hope!), is it possible that we can agree to disagree? Of course, in the… Continue reading Paper Review: Agreeing to Disagree
Readers of the blog will know that I am a fan of the Bayesian approach to probability. This approach is also sometimes called "personal probability", because it takes probabilities to be the degrees of belief (or credences) of rational agents. We can think of using probability like this as a framework for managing uncertainty in… Continue reading Paper Review: Difficulties in the Theory of Personal Probability
How should we change our beliefs in the light of new information? This is one of the central questions of epistemology, and has great practical importance. For example, consider a doctor who has a patient who is concerned he might have cancer. The doctor has certain beliefs: for example, she may think that her patient… Continue reading Paper Review: Why Conditionalize?
From climate change to vaccinations to the shape of the Earth (???!?!), scientific claims are often in dispute. Indeed, when encountering people who hold views against the (scientific) norm, we often think of them as "anti-scientific." Of course, the people who hold these views don't think they are being irrational. They think their position is… Continue reading Paper Review: “Antiscience Zealotry”? Values, Epistemic Risk, and the GMO Debate
Bayesian learning and decision theory (arguably) characterize rationality for idealized agents. However, carrying out Bayesian calculations can often be costly. In particular, the kind of agent one is--whether a human, lizard, or computer--constrains the kind of information processing one can do. This gestures towards a question: what is the relationship between idealized rationality and rationality… Continue reading Paper Review: Bayes, Bounds, and Rational Analysis