EFTA00650173.pdf
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From: Joscha Bach
To: Jeffrey Epstein <jeevacation@gmail.com>
Subject: Re: Decision making
Date: Wed, 26 Aug 2015 20:44:19 +0000
So you are suggesting that probabilities are not the best way to frame decision making? (We can overcome things
like independence, at the cost of sufficiently complex models, and in a world without repetition = some kind of
regularity, all bets are off, but of course probabilistic models might still be impractical in practice.) What would
be a better framework?
Am 26.08.2015 um 16:39 schrieb jeffrey E. <jeevacation@gmail.com>:
probablities vs similiarities. I suggest you take care with the concept of probabilites which really requires
repetition, symmetry, and independence.
On Wed, Aug 26, 2015 at 4:26 PM, Joscha Bach <joscha.bach@gmail.com> wrote:
I. Does luck mean gambling, or getting the probabilities right by intuition?
2. What else tells you anything about the future? (The past also tells us how much is does not tell us about
the future)
Am 26.08.2015 um 16:23 schrieb jeffrey E. <reevacation@gmail.com>:
luck plays a role. 2, looking back ( bayesian ) might not tell you anthing about the future.
On Wed, Aug 26, 2015 at 3:44 PM, Joscha Bach <
> wrote:
Re motivation: Have you seen the recent movie "Ex Machina"? I liked it; one of the few Al movies that
have not been dumbed down. The main character is a beautiful female looking Al, clearly intelligent, and
able to manipulate humans to an arbitrary degree. What makes her inhuman is that she is probably
motivated by a single principle, like option maximization. That would make her an inscrutable
psychopath. Option maximization would entail energy, physical integrity, perhaps reproduction, certainly
learning, but you will have an agent that you won't like to share a prisoner's dilemma with.
How do you approach decision making? I have recently learned that people that subscribe for Cryonics
(freezing one's head or body in the hope to be revived when future technologies make it possible) assign
a lower probability to that it works than the general population. But whereas "normal" people tend to
make binary models about the world: something is "probably not going to work, so let us not bother",
many of the Cryonics folks will argue that paying $500 a month for a 1% chance of immortality seems
like a bargain.
This seems to generalize: in principle, we should perform a Bayesian approximation for all our major
decisions, attach probability distributions to everything in the space of possible beliefs, and be able to
outperform the vast majority of folks that relies on narratives (i.e. binary yes/no decisions about the facts
in the world). Gigerenzer, Kahnemann and many others have shown that human brains are terrible of
getting this intuitively right, to the point where an absence of fine-grained domain knowledge often leads
to better management decisions etc.
The divide between probabilistic models vs. narrative models is reflected to some degree in the conflict
between probabilistic and logic based Al. In practice, we will probably need to combine both, but I
wonder if there is an intrinsic limit to probabilistic descriptions in a highly complex world, where we
EFTA00650173
cannot observe baseline probabilities anyway.
How do you decide? Do you Solomonoff-induce and Bayes the hell out of the stock market, do you
reason, do you soak up data and let your intuitions guide you, or is most of the important stuff depending
on communication and negotiation? Is there are general approach, or how much should theories of
decision making be dependent on the domain?
Cheers,
Joscha
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and may be unlawful. If you have received this
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EFTA00650174
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| Filename | EFTA00650173.pdf |
| File Size | 151.4 KB |
| OCR Confidence | 85.0% |
| Has Readable Text | Yes |
| Text Length | 4,843 characters |
| Indexed | 2026-02-11T23:18:09.753837 |