↑ 16 References
In rationality, from a to z, eliezer yudkowsky often describes how rationality (more or less what I call probabilistic thinking) can be like a martial art. It is an interesting comparison, though I don’t know if I agree with all parts of it.
Whatever you want, I suppose. Even if it doesn’t matter, life is still some sort of game. I submit probabilistic thinking as the first attempt to answer how to play the game better.
probabilistic thinking requires thinking mathematically, at least in broad strokes. I’ll try to map out the technical underpinnings of probabilistic thinking.
Can probabilistic thinking be a unified theory for reason and belief updating? It would need to fully subordinate bayes’ theorem and solomonoff induction (the latter of which may already be a unified theory of its own).
Growing Thoughts
These are still very raw and undeveloped, but have a lot of content connected to them. Currently, both these growing thoughts seem to fall under the umbrella of think more scientifically, and more morally.
Epistemology and category theory. Besides ethics, my philosophical interests have always lied in trying to find the underlying “physics” of how we think. This is partially why I always fascinated by computer science, and from there my interest in functional programming lead me to category theory. I am super interested in continuing to explore what fundamental concepts make up our thoughts, our language, and the systems that we build as humans. Additionally, I would consider myself a bayesian and believe we can do a lot to improve the way we think about the world by adopting a probabilistic, bayesian-oriented lens on reality. This interest has also been connected to my interest in synthesizing knowledge and knowledge graphs generally, and is why I have been publishing a subset of my personal notes on my website (denizaydemir.com).
Right now to me, it feels like teaching Statistics and Probability to students that aren’t using the fields professionally is less effective than teaching them probabilistic thinking (i.e. practical Bayes)