The most common formalizations of Occam's Razor, Solomonoff induction and Minimum Description Length, measure the program size of a computation used in a hypothesis, but don't measure the running time or space requirements of the computation. What if this makes a mind vulnerable to finite forms of Pascal's Wager? A compactly specified wager can grow in size much faster than it grows in complexity. The utility of a Turing machine can grow much faster than its prior probability shrinks.
Consider Knuth's up-arrow notation:
- 3^3 = 3*3*3 = 27
- 3^^3 = (3^(3^3)) = 3^27 = 3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3*3 = 7625597484987
- 3^^^3 = (3^^(3^^3)) = 3^^7625597484987 = 3^(3^(3^(... 7625597484987 times ...)))
In other words: 3^^^3 describes an exponential tower of threes 7625597484987 layers tall. Since this number can be computed by a simple Turing machine, it contains very little information and requires a very short message to describe. This, even though writing out 3^^^3 in base 10 would require enormously more writing material than there are atoms in the known universe (a paltry 10^80).
Now suppose someone comes to me and says, "Give me five dollars, or I'll use my magic powers from outside the Matrix to run a Turing machine that simulates and kills 3^^^^3 people."
Call this Pascal's Mugging.
"Magic powers from outside the Matrix" are easier said than done - we have to suppose that our world is a computing simulation run from within an environment that can afford simulation of arbitrarily large finite Turing machines, and that the would-be wizard has been spliced into our own Turing tape and is in continuing communication with an outside operator, etc.
Thus the Kolmogorov complexity of "magic powers from outside the Matrix" is larger than the mere English words would indicate. Therefore the Solomonoff-inducted probability, two to the negative Kolmogorov complexity, is exponentially tinier than one might naively think.
But, small as this probability is, it isn't anywhere near as small as 3^^^^3 is large. If you take a decimal point, followed by a number of zeros equal to the length of the Bible, followed by a 1, and multiply this unimaginably tiny fraction by 3^^^^3, the result is pretty much 3^^^^3.
Most people, I think, envision an "infinite" God that is nowhere near as large as 3^^^^3. "Infinity" is reassuringly featureless and blank. "Eternal life in Heaven" is nowhere near as intimidating as the thought of spending 3^^^^3 years on one of those fluffy clouds. The notion that the diversity of life on Earth springs from God's infinite creativity, sounds more plausible than the notion that life on Earth was created by a superintelligence 3^^^^3 bits large. Similarly for envisioning an "infinite" God interested in whether women wear men's clothing, versus a superintelligence of 3^^^^3 bits, etc.
The original version of Pascal's Wager is easily dealt with by the gigantic multiplicity of possible gods, an Allah for every Christ and a Zeus for every Allah, including the "Professor God" who places only atheists in Heaven. And since all the expected utilities here are allegedly "infinite", it's easy enough to argue that they cancel out. Infinities, being featureless and blank, are all the same size.
But suppose I built an AI which worked by some bounded analogue of Solomonoff induction - an AI sufficiently Bayesian to insist on calculating complexities and assessing probabilities, rather than just waving them off as "large" or "small".
If the probabilities of various scenarios considered did not exactly cancel out, the AI's action in the case of Pascal's Mugging would be overwhelmingly dominated by whatever tiny differentials existed in the various tiny probabilities under which 3^^^^3 units of expected utility were actually at stake.
You or I would probably wave off the whole matter with a laugh, planning according to the dominant mainline probability: Pascal's Mugger is just a philosopher out for a fast buck.
But a silicon chip does not look over the code fed to it, assess it for reasonableness, and correct it if not. An AI is not given its code like a human servant given instructions. An AI is its code. What if a philosopher tries Pascal's Mugging on the AI for a joke, and the tiny probabilities of 3^^^^3 lives being at stake, override everything else in the AI's calculations? What is the mere Earth at stake, compared to a tiny probability of 3^^^^3 lives?
How do I know to be worried by this line of reasoning? How do I know to rationalize reasons a Bayesian shouldn't work that way? A mind that worked strictly by Solomonoff induction would not know to rationalize reasons that Pascal's Mugging mattered less than Earth's existence. It would simply go by whatever answer Solomonoff induction obtained.
It would seem, then, that I've implicitly declared my existence as a mind that does not work by the logic of Solomonoff, at least not the way I've described it. What am I comparing Solomonoff's answer to, to determine whether Solomonoff induction got it "right" or "wrong"?
Why do I think it's unreasonable to focus my entire attention on the magic-bearing possible worlds, faced with a Pascal's Mugging? Do I have an instinct to resist exploitation by arguments "anyone could make"? Am I unsatisfied by any visualization in which the dominant mainline probability leads to a loss? Do I drop sufficiently small probabilities from consideration entirely? Would an AI that lacks these instincts be exploitable by Pascal's Mugging?
Is it me who's wrong? Should I worry more about the possibility of some Unseen Magical Prankster of very tiny probability taking this post literally, than about the fate of the human species in the "mainline" probabilities?
It doesn't feel to me like 3^^^^3 lives are really at stake, even at very tiny probability. I'd sooner question my grasp of "rationality" than give five dollars to a Pascal's Mugger because I thought it was "rational".
Should we penalize computations with large space and time requirements? This is a hack that solves the problem, but is it true? Are computationally costly explanations less likely? Should I think the universe is probably a coarse-grained simulation of my mind rather than real quantum physics, because a coarse-grained human mind is exponentially cheaper than real quantum physics? Should I think the galaxies are tiny lights on a painted backdrop, because that Turing machine would require less space to compute?
Given that, in general, a Turing machine can increase in utility vastly faster than it increases in complexity, how should an Occam-abiding mind avoid being dominated by tiny probabilities of vast utilities?
If I could formalize whichever internal criterion was telling me I didn't want this to happen, I might have an answer.
I talked over a variant of this problem with Nick Hay, Peter de Blanc, and Marcello Herreshoff in summer of 2006. I don't feel I have a satisfactory resolution as yet, so I'm throwing it open to any analytic philosophers who might happen to read Overcoming Bias.
Number one is a very good point, but I don't think the conclusion would necessarily follow:
1: You always may need outside information to solve the problem. For instance, If I am looking for a Key to Room 3, under the assumption that it is in Room 1 because I saw someone drop it in Room 1, I cannot search only Room 1 and never search Room 2 and find the key in all cases because there may be a way for the key to have moved to Room 2 without my knowledge.
For instance, as an example of something I might expect, the Mouse could have grabbed it and quietly went back to it's nest in Room 2. Now, that's something I would expect, so while searching for the key I should also note any mice I see. They might have moved it.
But I also have to have a method for handling situations I would not expect. Maybe the Key activated a small device which moved it to room 2 through a hidden passage in the wall which then quietly self destructed, leaving no trace of the device that is within my ability to detect in Room 1. (Plenty of traces were left in Room 2, but I can't see Room 2 from Room 1.) That is an outside possibility. But it doesn't break laws of physics or require incomprehensible technology that it could have happened.
2: There are also a large number of alternative thought experiments which have massive expected utility gain. Because of the Halting problem, I can't necessarily determine how long it is going to take to figure these problems out, if they can be figured out. If I allow myself to get stuck on any one problem, I may have picked an unsolvable one, while the NEXT problem with a massive expected utility gain is actually solvable. under that logic, it's still bad to spend all my time thinking about one particular question.
3: Thanks to Paralellism, it is entirely possible for a program to run multiple different problems all at the same time. Even I can do this to a lesser extent. I can think about a Philosophy problem and also eat at the same time. A FAI running into a Pascal's Mugger could begin weighing the utility of giving in to the mugging, ignoring the mugging, attempting to knock out the mugger, or simply saying: "Let me think about that. I will let you know when I have decided to give you the money or not and will get back to you." all at the same time.
Having reviewed this discussion, I realize that I may just be restating of the problem going on here. A lot of the proposed situations I'm discussing seem to have a "But what if this OTHER situation exists and the utilities indicate you pick the counter intuitive solution? But what if this OTHER situation exists and the utilities indicate you pick the intuitive solution?"
To approach the problem more directly, Maybe it would be a better approach might be to consider Gödel's incompleteness theorems. Quoting from wikipedia:
"The first incompleteness theorem states that no consistent system of axioms whose theorems can be listed by an "effective procedure" (essentially, a computer program) is capable of proving all facts about the natural numbers. For any such system, there will always be statements about the natural numbers that are true, but that are unprovable within the system."
If the FAI in question is considering utility in terms of natural numbers, It seems to make sense that there are things it should do to maximize utility that it would not be able to prove inside it's system. So to take into account that, we would have to design it to call for help in the case of situations which had the appearance of being likely to be unprovable.
Based on Alan Turings solution of the Halting problem again, If the FAI can only be treated as a Turing Machine, it can't establish whether or not some situations are provable. That seems like it means it would have to at some point have some kind of hard point to do something like "Call for help and do nothing but call for help if you have been running for one hour and can't figure this out." or alternatively "Take an action based on your current guess of the probabilities if you can't figure this out after one hour, and if at least one of the two probabilities is still incalculable, choose randomly."
This is again getting a bit long, so I'll stop writing for a bit to double check that this seems reasonable and that I didn't miss something.
You seem to be going far afield. The technical conclusion of the first argument is that one should spend all one's resources dealing with cases with infinite or very high utility, even if they are massively improbable. The way I said it earlier was imprecise.
When humans deal with a problem they can't solve, they guess. It should not be difficult to build an AI that can solve everything humans can solve. I think the "solution" to Godelization is a mathematical intuition module that finds rough guesses, not asking another agent. What special powers does the other agent have? Why can't the AI just duplicate them.