I think I'm starting to get this. Is this because it uses heuristics to model the world, with humans in it too?
Yes, that's actually the reason why I wanted to tackle the "treacherous turn" first, to look for a general design that would allow us to trust the results from tests and then build on that. I'm seeing as order of priority:
1) make sure we don't get tricked, so that we can trust the results of what we do;
2) make the AI do the right things.
I'm referring to 1) in here.
Also, as mentioned in another comment to the main post, part of the AI's utility function is evolving to understand human values, so I still don't quite see why exactly it shouldn't work. I envisage the utility function as being the union of two parts, one where we have described the goal for the AI, which shouldn't be changed with iterations, and another with human values, which will be learnt and updated. This total utility function is common to all agents, including the AI.
Hi Vaniver, yes my point is exactly that of creating honesty, because that would at least allow us to test reliably so it sounds like it should be one of the first steps to aim for. I'll just write a couple of lines to specify my thought a little further, which is to design an AI that: 1- uses an initial utility function U, defined in absolute terms rather than subjective terms (for instance "survival of the AI" rather than "my survival"); 2- doesn't try to learn another utility function for humans or for other agents, but uses for everyone the same utility function U it uses for itself; 3- updates this utility function when things don't go to plan, so that it improves its predictions of reality. In order to do this, this "universal" utility function would need to be the result of two parts: 1) the utility function that we initially gave the AI to describe its goal, which I suppose should be unchangeable, and 2) the utility function with the values that it is learning after each iteration, which hopefully should eventually resemble human values as that would make its plans work better eventually. I'm trying to understand whether such a design is technically feasible and whether it would work in the intended way? Am I right in thinking that it would make the AI "transparent", in the sense that it would have no motivation to mislead us. Also wouldn't this design make the AI indifferent to our actions, which is also desirable? Seems to me like it would be a good start. It's true that different people would have different values, so I'm not sure about how to deal with that. Any thought?
Hi ChristianKI, thanks, I'll try to find the article. Just to be clear though I'm not suggesting to hardcode values, I'm suggesting to design the AI so that it uses for itself and for us the same utility function and updates it as it gets smarter. It sounds from the comments I'm getting that this is technically not feasible so I'll aim at learning exactly how an AI works in detail and maybe look for a way to maybe make it feasible. If this was indeed feasible, would I be right in thinking it would not be motivated to betray us or am I missing something there as well? Thanks for your help by the way!
Yes I think 2) is closer to what I'm suggesting. Effectively what I am thinking is what would happen if, by design, there was only one utility function defined in absolute terms (I've tried to explaine this in the latest open thread), so that the AI could never assume we would disagree with it. By all means, as it tries to learn this function, it might get it completely wrong, so this certainly doesn't solve the problem of how to teach it the right values, but at least it looks to me that with such a design it would never be motivated to lie to us because it would always think we would be in perfect agreement. Also, I think it would make it indifferent to our actions as it would always assume we would follow the plan from that point onward. The utility function it uses (same for itself and for us) would be the union of a utility function that describes the goal we want it to achieve, which would be unchangeable, and the set of values it is learning after each iteration. I'm trying to understand what would be wrong with this design, cause to me it looks like we would have achieved an honest AI, which is a good start.
Sorry for my misused terminology. Is it not feasible to design it with those characteristics?
mmm I see. So maybe we should have coded it so that it cared for paperclips and for an approximation of what we also care about, then on observation it should update its belief of what to care about, and by design it should always assume we share the same values?
Hi all, thanks for taking your time to comment. I'm sure it must be a bit frustrating to read something that lacks technical terms as much as this post, so I really appreciate your input. I'll just write a couple of lines to summarize my thought, which is to design an AI that:
1- uses an initial utility function U, defined in absolute terms rather than subjective terms (for instance "survival of the AI" rather than "my survival");
2- doesn't try to learn an utility function for humans or for other agents, but uses for everyone the same utility function U it uses for itself;
3- updates this utility function when things don't go to plan, so that it improves its predictions.
Is such a design technically feasible? Am I right in thinking that it would make the AI "transparent", in the sense that it would have no motivation to mislead us. Also wouldn't this design make the AI indifferent to our actions, which is also desirable?
It's true that different people would have different values, so I'm not sure about how to deal with that. Any thought?
I see. But rather than dropping this clause, shouldn't it try to update its utility function in order to improve its predictions? If we somehow hard-coded the fact that it can only ever apply its own utility function, then it wouldn't have other choice than updating that. And the closer it gets to our correct utility function, the better it is at predicting reality.
Yes that's what would happen if the AI tries to build a model for humans. My point is that if it was to instead simply assume humans were an exact copy of itself, so same utility function and same intellectual capabilities it would assume that they would reach the same exact same conclusions and therefore wouldn't need any forcing, nor any tricks.