Private_messaging, can you explain why you open up with such a hostile question at eli? Why the implied insult? Is that the custom here? I am new, should I learn to do this?
For example, I could have opened with your same question, because Monte Carlo methods are very different from what you describe (I happened to be a mathematical physicist back in the day). Let me quote an actual definition:
Monte Carlo Method: A problem solving technique used to approximate the probability of certain outcomes by running multiple trial runs, called simulations, using random variables.
A classic very very simple example is a program that approximates the value of 'pi' thusly:
(loop here for as many runs as you like) { define variables $x,$y, $hits_inside_radius = 0, $radius =1.0, $total_hits=0, pi_approx;
input $total_hits for this run;
seed random function 'rand';
for (0..total_hits-1) do {
$x = rand(-1,1);
$y = rand(-1,1);
$hits_inside_radius++ if ( $x*$x + $y * $y <= 1.0);
}
$pi_approx = 4 * $hits_inside_radius
add $pi_approx and $total_hits to a nice output data vector or whatever
} output data for this particular run } print nice report exit();
OK, this is a nice toy Monte Carlo program for a specific problem. Real world applications typically have thousands of variables and explore things like strange attractors in high dimensional spaces, or particle physics models, or financial programs, etc. etc. It's a very powerful methodology and very well known.
In what way is this little program an instance of throwing a lot of random programs at the problem of approximating 'pi'? What would your very stupid evolutionary program to solve this problem more efficiently be? I would bet you a million dollars to a thousand (if I had a million) that my program would win a race against a very stupid evolutionary program to estimate pi to six digits accurately, that you write. Eli and Eliezer can judge the race, how is that?
I am sorry if you feel hurt by my making fun of your ignorance of Monte Carlo methods, but I am trying to get in the swing of the culture here and reflect your cultural norms by copying your mode of interaction with Eli, that is, bullying on the basis of presumed superior knowledge.
If this is not pleasant for you I will desist, I assume it is some sort of ritual you enjoy and consensual on Eli's part and by inference, yours, that you are either enjoying this public humiliation masochistically or that you are hoping people will give you aversive condition when you publicly display stupidity, ignorance, discourtesy and so on. If I have violated your consent then I plead that I am from a future where this is considered acceptable when a person advertises that they do it to others. Also, I am a baby eater and human ways are strange to me.
OK. Now some serious advice:
If you find that you have just typed "Do you even know what X is?" then given a little condescending mini lecture about X, please check that you yourself actually know what X is before you post. I am about to check Wikipedia before I post in case I'm having a brain cloud, and i promise that I will annotate any corrections I need to make after I check; everything up to HERE was done before the check. (Off half recalled stuff from grad school a quarter century ago...)
OK, Wikipedia's article is much better than mine. But I don't need to change anything, so I won't.
P.S. It's ok to look like an idiot in public, it's a core skill of rationalists to be able to tolerate this sort of embarassment, but another core skill is actually learning something if you find out that you were wrong. Did you go to Wikipedia or other sources? Do you know anything about Monte Carlo Methods now? Would you like to say something nice about them here?
P.P.S. Would you like to say something nice about eli_sennesh, since he actually turns out to have had more accurate information than you did when you publicly insulted his state of knowledge? If you too are old pals with a joking relationship, no apology needed to him, but maybe an apology for lazily posting false information that could have misled naive readers with no knowledge of Monte Carlo methods?
P.P.P.S. I am curious, is the psychological pleasure of viciously putting someone else down as ignorant in front of their peers worth the presumed cost of misinforming your rationalist community about the nature of an important scientific and mathematical tool? I confess I feel a little pleasure in twisting the knife here, this is pretty new to me. Should I adopt your style of intellectual bullying as a matter of course? I could read all your posts and viciously hold up your mistakes to the community, would you enjoy that?
I'm well aware of what Monte Carlo methods are (I work in computer graphics where those are used a lot), I'm also aware of what AIXI does.
Furthermore eli (and the "robots are going to kill everyone" group - if you're new you don't even know why they're bringing up monte-carlo AIXI in the first place) are being hostile to TheAncientGeek.
edit: to clarify, Monte-Carlo AIXI is most assuredly not an AI which is inventing and applying some clever Monte Carlo methods to predict the environment. No, it's estimating the sum over all predictors of environ...
tl;dr An unconstrained search through possible future worlds is a dangerous way of choosing positive outcomes. Constrained, imperfect or under-optimised searches work better.
Some suggested methods for designing AI goals, or controlling AIs, involve unconstrained searches through possible future worlds. This post argues that this is a very dangerous thing to do, because of the risk of being tricked by "siren worlds" or "marketing worlds". The thought experiment starts with an AI designing a siren world to fool us, but that AI is not crucial to the argument: it's simply an intuition pump to show that siren worlds can exist. Once they exist, there is a non-zero chance of us being seduced by them during a unconstrained search, whatever the search criteria are. This is a feature of optimisation: satisficing and similar approaches don't have the same problems.
The AI builds the siren worlds
Imagine that you have a superintelligent AI that's not just badly programmed, or lethally indifferent, but actually evil. Of course, it has successfully concealed this fact, as "don't let humans think I'm evil" is a convergent instrumental goal for all AIs.
We've successfully constrained this evil AI in a Oracle-like fashion. We ask the AI to design future worlds and present them to human inspection, along with an implementation pathway to create those worlds. Then if we approve of those future worlds, the implementation pathway will cause them to exist (assume perfect deterministic implementation for the moment). The constraints we've programmed means that the AI will do all these steps honestly. Its opportunity to do evil is limited exclusively to its choice of worlds to present to us.
The AI will attempt to design a siren world: a world that seems irresistibly attractive while concealing hideous negative features. If the human mind is hackable in the crude sense - maybe through a series of coloured flashes - then the AI would design the siren world to be subtly full of these hacks. It might be that there is some standard of "irresistibly attractive" that is actually irresistibly attractive: the siren world would be full of genuine sirens.
Even without those types of approaches, there's so much manipulation the AI could indulge in. I could imagine myself (and many people on Less Wrong) falling for the following approach:
The longer I stare into this world, the greater an understanding I get of my own values. And this is just the starting point: the world subtly opens up new avenues of philosophical musings in my brain, the images I see triggering me to come up with my own insights and thought experiments as to the meaning of goodness - insights that are then carefully confirmed as I did deeper. I could stay staring at this wonderful, beautiful and complex world for hours, days, years, gaining a deeper wisdom and understanding as I go, truly appreciating how the mysteries of this place unravel into new versions of worth and goodness. Every time I ever have a doubt about it, that doubt is systemically resolved into a new glorious confirmation of how much the AI really gets what I value, even before I knew how much I valued it.
Meanwhile, at some level of complexity safely beyond what my human mind will ever reach, the AI is hiding all the evil and unmitigated suffering.
Your siren world may differ from mine - you may be vulnerable to different tricks. Since people often believe they would be immune to such manipulation, feel free to imagine that the AI is fooling someone else - we know how stupid other people can be, right? - while you watch as a helpless bystander.
The problem is that a future universe is likely to be vast and complicated. When inspecting it, we have certain inspection criteria (IC). These consist of our values and preferences, but also the ways we would look into this universe, how we would follow up on initial impressions, various measures and yardsticks we might use to summarise the data we see, all the clever and devious plans we might come up with to ferret out "what's really going on". These IC are going to be considerably simpler than the totality of the future universe. So the AI's task is to optimise a universe design that passes the IC, while shoving in as much disutility as it can - which in a large universe, is a tremendous amount. Unless our IC are perfect and already include a good solution to the problem of value (in which case we've solved the friendliness problem already), a superintelligent AI will likely succeed at its task.
Siren and marketing worlds without builders
The above thought experiment needed a superintelligent evil AI for the design of the siren world. But if we admit that that is possible, we don't actually need the AI any more. The siren worlds exist: there are potential worlds of extreme disutility that satisfie our IC. If we simply did an unconstrained search across all possible future worlds (something like the search in Paul Christiano's indirect normativity - an idea that inspired the siren world concept), then we would at some point find siren worlds. And if we took the time to inspect them, we'd get sucked in by them.
How bad is this problem in general? A full search will not only find the siren worlds, but also a lot of very-seductive-but-also-very-nice worlds - genuine eutopias. We may feel that it's easier to be happy than to pretend to be happy (while being completely miserable and tortured and suffering). Following that argument, we may feel that there will be far more eutopias than siren worlds - after all, the siren worlds have to have bad stuff plus a vast infrastructure to conceal that bad stuff, which should at least have a complexity cost if nothing else. So if we chose the world that best passed our IC - or chose randomly among the top contenders - we might be more likely to hit a genuine eutopia than a siren world.
We are both superintelligences. You have a bunch of independently happy people that you do not aggressively compel. I have a group of zombies - human-like puppets that I can make do anything, appear to feel anything (though this is done sufficiently well that outside human observers can't tell I'm actually in control). An outside human observer wants to check that our worlds rank high on scale X - a scale we both know about.
Which of us do you think is going to be better able to maximise our X score?
This can also be seen as a epistemic version of Goodhart's law: "When a measure becomes a target, it ceases to be a good measure." Here the IC are the measure, and the marketing worlds are targeting them, and hence they cease to be a good measure. But recall that the IC include the totality of approaches we use to rank these worlds, so there's no way around this problem. If instead of inspecting the worlds, we simply rely on some sort of summary function, then the search will be optimised to find anything that can fool/pass that summary function. If we use the summary as a first filter, then apply some more profound automated checking, then briefly inspect the outcome so we're sure it didn't go stupid - then the search will optimised for "pass the summary, pass automated checking, seduce the inspector".
Different IC therefore will produce different rankings of worlds, but the top worlds in any of the ranking will be marketing worlds (and possibly siren worlds).
Constrained search and satisficing our preferences
The issue is a problem of (over) optimisation. The IC correspond roughly with what we want to value, but differs from it in subtle ways, enough that optimising for one could be disastrous for the other. If we didn't optimise, this wouldn't be a problem. Suppose we defined an acceptable world as one that we would judge "yeah, that's pretty cool" or even "yeah, that's really great". Then assume we selected randomly among the acceptable worlds. This would probably result in a world of positive value: siren worlds and marketing worlds are rare, because they fulfil very specific criteria. They triumph because they score so high on the IC scale, but they are outnumbered by the many more worlds that are simply acceptable.
This is in effect satisficing over the IC, rather than optimising over them. Satisficing has its own issues, however, so other approaches could be valuable as well. One way could be use constrained search. If for instance we took a thousand random worlds and IC-optimised over them, we're very unlikely to encounter a siren or marketing world. We're also very unlikely to encounter a world of any quality, though; we'd probably need to IC-optimise over at least a trillion worlds to find good ones. There is a tension in the number: as the number of worlds searched increases, their quality increases, but so does the odds of encountering a marketing or siren world. EDIT: Lumifer suggested using a first-past-the-post system: search through worlds, and pick the first acceptable one we find. This is better than the approach I outlined in this paragraph.
We could also restrict the search by considering "realistic" worlds. Suppose we had to take 25 different yes-no decisions that could affect the future of the humanity. This might be something like "choosing which of these 25 very different AIs to turn on and let loose together" or something more prosaic (which stocks to buy, which charities to support). This results in 225 different future worlds to search through: barely more than 33 million. Because there are so few worlds, they are unlikely to contain a marketing world (given the absolutely crucial proviso that none of the AIs is an IC-optimiser!). But these worlds are not drawn randomly from the space of future worlds, but are dependent on key decisions that we believe are important and relevant. Therefore they are very likely to contain an acceptable world - or at least far more likely than a random set of 33 million worlds would be. By constraining the choices in this way, we have in effect satisficed without satisficing, which is both Zen and useful.
As long as we're aware of the problem, other approaches may also allow for decent search without getting sucked in by a siren or a marketer.