Im sympathetic to the argument, and I’d go so far as to say: Predictability is so low, the EV of most possible actions is zero (partially due to symmetry, I think cluelessness gets this ~ wrong) unless I manage to find a small pocket of predictability of how my actions meaningfully impact the world. So I’m largely very short-termist in what I do. Is this different to what you’re saying here?
Yes this was clear - imho you underestimate how sophisticated investors in hedge funds (what you call “clients”) are. The best hedge funds charge way more than 2% and it can still be a rational investment. “Value to society” is not a criterion that matters. “Value to investors” is.
There are many mutual funds that charge over 1%, add little value and target unsophisticated investors. That’s the case where I buy your point.
Yeah I think the obvious Bayesian reply is: Just make your prior less informative if you know less? It’s fine to choose it to be close to uniform over a very wide range if you know close to nothing.
I think the main concern is that people often use the expected value of such a wide distribution in utility maximisation. So the concerning part is the interaction between eg utilitarianism and Bayesian inference.
Bayesian inference and decision making are somewhat distinct steps. EV maxxing is a specific (and specifically simple) objective function that you can plug Bayesian estimates into for decision making. It removes the need to think about distributions.
I think it can be helpful to separate out the problems - eg I believe that there aren’t really any plausible alternatives to Bayesian inference (over future trajectories of the world as a function of your actions or similar) but I think there’s much more room for debate regarding the objective function.
Im sympathetic to the argument, and I’d go so far as to say: Predictability is so low, the EV of most possible actions is zero (partially due to symmetry, I think cluelessness gets this ~ wrong) unless I manage to find a small pocket of predictability of how my actions meaningfully impact the world.
So I’m largely very short-termist in what I do. Is this different to what you’re saying here?
How does diversification follow?
Intuitively this argument is made a lot, but the precise mechanism matters?
Yes this was clear - imho you underestimate how sophisticated investors in hedge funds (what you call “clients”) are. The best hedge funds charge way more than 2% and it can still be a rational investment. “Value to society” is not a criterion that matters. “Value to investors” is.
There are many mutual funds that charge over 1%, add little value and target unsophisticated investors. That’s the case where I buy your point.
Have you thought about including an automatic inflation adjustment?
Yeah I think the obvious Bayesian reply is: Just make your prior less informative if you know less? It’s fine to choose it to be close to uniform over a very wide range if you know close to nothing.
I think the main concern is that people often use the expected value of such a wide distribution in utility maximisation. So the concerning part is the interaction between eg utilitarianism and Bayesian inference.
People in EA should definitely read more Feyerabend! (Or ask llms what Feyerabend would say about a topic etc).
For example “a complete theory of scientific epistemology” is something he’d most likely reject even as an ideal.
Bayesian inference and decision making are somewhat distinct steps.
EV maxxing is a specific (and specifically simple) objective function that you can plug Bayesian estimates into for decision making. It removes the need to think about distributions.
I think it can be helpful to separate out the problems - eg I believe that there aren’t really any plausible alternatives to Bayesian inference (over future trajectories of the world as a function of your actions or similar) but I think there’s much more room for debate regarding the objective function.
The hedge fund industry is not based on this. Most hedge fund investors are sophisticated and they often pay more than 2%.
I see, fair.
What’s the alternative to “wide distribution stays wide?” in practice?
Separately, “very wrong and narrow prior” is a problem of course, but very much intra-Bayesian and not a criticism of Bayesian reasoning?
Nice distinction!
I’d agree that pop-Bayesianism is overused while more rigorous Bayesianism is underused.