agreed. To add on to this:

predictor doesn't use simulations/scanners of any sort but instead uses logic, and yet one-boxers still win.

It's worth pointing out that Newcomb's problem always takes the form of Simpson's paradox. The one boxers beat the two boxers as a whole, but among agents predicted to one-box, the two boxers win, and among agents predicted to two-box, the two boxers win.

The only reason to one-box is when your actions (which include both the final decision and the thoughts leading up to it) effect Omega's prediction. The general rule is: "Try to make Omega think you're one-boxing, but two-box whenever possible." It's just that in Newcomb's problem proper, fulfilling the first imperative requires actually one-boxing.

The trouble with real world examples is that we start introducing knowledge into the problem that we wouldn't ideally have. The psychologist's 75% success rate doesn't necessarily apply to you - in the real world you can make a different estimate than the one that is given. If you're an actor or a poker player, you'll have a much different estimate of how things are going to work out.

Psychologists are just messier versions of brain scanners - the fundamental premise is that they are trying to access your source code.

And what's more - suppose the predictions weren't made by accessing your source code? The direction of causality does matter. If Omega can predict the future, the causal lines flow backwards from your choice to Omega's past move. If Omega is scanning your brain, the causal lines go from your brain-state to Omega's decision. If there are no causal lines between your brain/actions and Omega's choice, you always two-box.

Real world example: what if I substituted your psychologist for a sociologist, who predicted you with above-chance accuracy using only your demographic factors? In this scenario, you aught to two-box - If you disagree, let me know and I can explain myself.

In the real world, you don't know to what extent your psychologist is using sociology (or some other factor outside your control). People can't always articulate why, but their intuition (correctly) begins to make them deviate from the given success% estimate as more of these real-world variables get introduced.

Oh, that's fair. I was thinking of "you don't know whether you're real or a simulation" as an intuitive way to prove the case for all "conscious" simulations. It doesn't have to be perfect - you could just as easily be an inaccurate simulation, with no way to know that you are a simulation and no way to know that you are inaccurate with respect to an original.

I was trying to get people to generalize downwards from the extreme intuitive example- Even with decreasing accuracy, as the simulation becomes so rough as to lose "consciousness" and "personhood", the argument keeps holding.

We don't need a perfect simulation for the purposes of this problem in the abstract - we just need a situation such that the problem-solver assigns better-than-chance predicting power to the Predictor, and a sufficiently high utility differential between winning and losing.

The "perfect whole brain simulation" is an extreme case which keeps things intuitively clear. I'd argue that any form of simulation which performs better than chance follows the same logic.

The only way to escape the conclusion via simulation is if you know something that Omega doesn't - for example, you might have some secret external factor modify your "source code" and alter your decision after Omega has finished examining you. Beating Omega essentially means that you need to keep your brain-state in such a form that Omega can't deduce that you'll two-box.

As Psychohistorian3 pointed out, the power that you've assigned to Omega predicting accurately is built into the problem. Your estimate of the probability that you will succeed in deception via the aforementioned method or any other is fixed by the problem.

In the real world, you are free to assign whatever probability you want to your ability to deceive Omega's predictive mechanisms, which is why this problem is counter intuitive.

You're saying that we live in a universe where Newcomb's problem is impossible because the future doesn't effect the past. I'll re-phrase this problem in such a way that it seems plausible in our universe:

I've got really nice scanning software. I scan your brain down to the molecule, and make a virtual representation of it on a computer. I run virtual-you in my software, and give virtual-you Newcomb's problem. Virtual-you answers, and I arrange my boxes according to that answer.

I come back to real-you. You've got no idea what's going on. I explain the scenario to you and I give you Newcomb's problem. How do you answer?

This particular instance of the problem does have an obvious, relatively uncomplicated solution: Lbh unir ab jnl bs xabjvat jurgure lbh ner rkcrevrapvat gur cneg bs gur fvzhyngvba, be gur cneg bs gur syrfu-naq-oybbq irefvba. Fvapr lbh xabj gung obgu jvyy npg vqragvpnyyl, bar-obkvat vf gur fhcrevbe bcgvba.

If for any reason you suspect that the Predictor can reach a sufficient level of accuracy to justify one-boxing, you one box. It doesn't matter what sort of universe you are in.

Relative to UFAI, FAI work seems like it would be mathier and more insight-based, where UFAI can more easily cobble together lots of pieces. This means that UFAI parallelizes better than FAI. UFAI also probably benefits from brute-force computing power more than FAI. Both of these imply, so far as I can tell, that slower economic growth is good news for FAI; it lengthens the deadline to UFAI and gives us more time to get the job done.

Forgive me if this is a stupid question, but wouldn't UFAI and FAI have identical or near-identical computational abilities/methods/limits and differ only by goals/values?