Expected utility maximization is a tool in your mental toolbox that helps clarify your thinking, not something that you'd try to carry out explicitly.
http://lesswrong.com/lw/sg/when_not_to_use_probabilities/ :
I don't always advocate that human beings, trying to solve their problems, should try to make up verbal probabilities, and then apply the laws of probability theory or decision theory to whatever number they just made up, and then use the result as their final belief or decision.
The laws of probability are laws, not suggestions, but often the true Law is too difficult for us humans to compute. If P != NP and the universe has no source of exponential computing power, then there are evidential updates too difficult for even a superintelligence to compute - even though the probabilities would be quite well-defined, if we could afford to calculate them.
So sometimes you don't apply probability theory. Especially if you're human, and your brain has evolved with all sorts of useful algorithms for uncertain reasoning, that don't involve verbal probability assignments.
Not sure where a flying ball will land? I don't advise trying to formulate a probability distribution over its landing spots, performing deliberate Bayesian updates on your glances at the ball, and calculating the expected utility of all possible strings of motor instructions to your muscles.
Trying to catch a flying ball, you're probably better off with your brain's built-in mechanisms, then using deliberative verbal reasoning to invent or manipulate probabilities.
Our brains already do expected utility maximization, or something approximating it, automatically and subconsciously. There's no need to try - or use - in trying to override those calculations with explicit reasoning if it's not necessary.
So when do we use the principle of expected utility? Mostly, when dealing with abstract issues that our brains haven't evolved to deal with. Investing, deciding whether to buy insurance, donating to charity, knowing not to play the lottery, that sort of thing. It also lends itself to some useful heuristics: for instance, Bryan Caplan points out that
The truth about essay contests is that the number of submissions is usually absurdly low considering the size of the prizes and the opportunity cost of students' time.
And that's really an expected utility calculation: your chances of winning in an essay contest might be pretty low, but so is your cost of attending, and the prizes are large enough to make the expected utility positive. That kind of thing.
Our brains already do expected utility maximization, or something approximating it, automatically and subconsciously.
Or something that expected utility maximization is an approximation of.
I would like to ask for help on how to use expected utility maximization, in practice, to maximally achieve my goals.
As a real world example I would like to use the post 'Epistle to the New York Less Wrongians' by Eliezer Yudkowsky and his visit to New York.
How did Eliezer Yudkowsky compute that it would maximize his expected utility to visit New York?
It seems that the first thing he would have to do is to figure out what he really wants, his preferences1, right? The next step would be to formalize his preferences by describing it as a utility function and assign a certain number of utils2 to each member of the set, e.g. his own survival. This description would have to be precise enough to figure out what it would mean to maximize his utility function.
Now before he can continue he will first have to compute the expected utility of computing the expected utility of computing the expected utility of computing the expected utility3 ... and also compare it with alternative heuristics4.
He then has to figure out each and every possible action he might take, and study all of their logical implications, to learn about all possible world states he might achieve by those decisions, calculate the utility of each world state and the average utility of each action leading up to those various possible world states5.
To do so he has to figure out the probability of each world state. This further requires him to come up with a prior probability for each case and study all available data. For example, how likely it is to die in a plane crash, how long it would take to be cryonically suspended from where he is in case of a fatality, the crime rate and if aliens might abduct him (he might discount the last example, but then he would first have to figure out the right level of small probabilities that are considered too unlikely to be relevant for judgment and decision making).
I probably miss some technical details and got others wrong. But this shouldn't detract too much from my general request. Could you please explain how Less Wrong style rationality is to be applied practically? I would also be happy if you could point out some worked examples or suggest relevant literature. Thank you.
I also want to note that I am not the only one who doesn't know how to actually apply what is being discussed on Less Wrong in practice. From the comments:
I can't help but agree.
P.S. If you really want to know how I feel about Less Wrong then read the post 'Ontological Therapy' by user:muflax.
1. What are "preferences" and how do you figure out what long-term goals are stable enough under real world influence to allow you to make time-consistent decisions?
2. How is utility grounded and how can it be consistently assigned to reflect your true preferences without having to rely on your intuition, i.e. pull a number out of thin air? Also, will the definition of utility keep changing as we make more observations? And how do you account for that possibility?
3. Where and how do you draw the line?
4. How do you account for model uncertainty?
5. Any finite list of actions maximizes infinitely many different quantities. So, how does utility become well-defined?