You can construct a set of values and a utility function to fit your observed behavior, no matter how your brain produces that behavior.
I’m deeply hesitant to jump into a debate that I don’t know the history of, but...
Isn’t it pretty generally understood that this is not true? The Utility Theory folks showed that behavior of an agent can be captured by a numerical utility function iff the agent’s preferences conform to certain axioms, and Allais and others have shown that human behavior emphatically does not.
Seems to me that if human behavior were in general able to be captured by a utility function, we wouldn’t need this website. We’d be making the best choices we could, given the information we had, to maximize our utility, by definition. In other words, “instrumental rationality” would be easy and automatic for everyone. It’s not, and it seems to me a big part of what we can do to become more rational is try and wrestle our decision-making algorithms around until the choices they make are captured by some utility function. In the meantime, the fact that we’re puzzled by things like moral dilemmas looks like a symptom of irrationality.
Introduction to Neuroscience
Recommendation: Neuroscience:Exploring the Brain by Bear, Connors, Paradiso
Reasons: BC&P is simply much better written, more clear, and intelligible than it’s competitors Neuroscience by Dale Purves and Fundamentals of Neural Science by Eric Kandel. Purves covers almost the same ground, but is just not written well, often just listing facts without really attempting to synthesize them and build understanding of theory. Bear is better than Purves in every regard. Kandel is the Bible of the discipline, at 1400 pages it goes into way more depth than either of the others, and way more depth than you need or will be able to understand if you’re just starting out. It is quite well-written, but it should be treated more like an encyclopedia than a textbook.
I also can’t help recommending Theoretical Neuroscience by Peter Dayan and Larry Abbot, a fantastic introduction to computational neuroscience, Bayesian Brain, a review of the state of the art of baysian modeling of neural systems, and Neuroeconomics by Paul Glimcher, a survey of the state of the art in that field, which is perhaps the most relevant of all of this to LW-type interests. The second two are the only books of their kind, the first has competitors in Computational Explorations in Cognitive Neuroscience by Randall O’Reilly and Fundamentals of Computational Neuroscience by Thomas Trappenberg, but I’ve not read either in enough depth to make a definitive recommendation.