I recently discussed the unlikelihood of an AI taking off and leaving the rest of society behind. The other part I mentioned of Singularitarian concern is that powerful AIs will be programmed with the wrong values. This would be bad even if the AIs did not take over the world entirely, but just became a powerful influence. Is that likely to happen?
Don’t get confused by talk of ‘values’. When people hear this they often think an AI could fail to have values at all, or that we would need to work out how to give an AI values. ‘Values’ just means what the AI does. In the same sense your refrigerator might value making things inside it cold (or for that matter making things behind it warm). Every program you write has values in this sense. It might value outputting ‘#t’ if and only if it’s given a prime number for instance.
The fear then is that a super-AI will do something other than what we want. We are unfortunately picky, and most things other than what we want, we really don’t want. Situations such as being enslaved by an army of giant killer robots, or having your job taken by a simulated mind are really incredibly close to what you do want compared to situations such as your universe being efficiently remodeled into stationery. If you have a machine with random values and the ability to manipulate everything in the universe, the chance of it’s final product having humans and tea and crumpets in it is unfathomably unlikely. Some SIAI members seem to believe that almost anyone who manages to make a powerful general AI will be so incapable of giving it suitable values as to approximate a random selection from mind design space.
The fear is not that whoever picks the AI’s goals will do so at random, but rather that they won’t forsee the extent of the AI’s influence, and will pick narrow goals that may as well be random when they act on the world outside the realm they were intended. For instance an AI programmed to like finding really big prime numbers might find methods that are outside the box, such as hacking computers to covertly divert others’ computing power to the task. If it improves its own intelligence immensely and copies itself we might quickly find ourselves amongst a race of superintelligent creatures whose only value is to find prime numbers. The first thing they would presumably do is stop this needless waste of resources worldwide on everything other than doing that.
Having an impact outside the intended realm is a problem that could exist for any technology. For a certain time our devices do what we want, but at some point they diverge if left long enough, depending on how well we have designed them to do what we want. In the past a car driving itself would diverge from what you wanted at the first corner, whereas after more work they diverge at the point another car gets in their way, and after more work they will diverge at the point that you unexpectedly need to pee.
Notice that at all stages we know over what realm the car’s values coincide with ours, and design it to run accordingly. The same goes with just about all the technology I can think of. Because your toaster’s values and yours diverge as soon as you cease to want bread heated, your toaster is programmed to turn off at that point and not to be very powerful.
Perhaps the concern about strong AI having the wrong goals is like saying ‘one day there will be cars that can drive themselves. It’s much easier to make a car that drives by itself than to make it steer well, so when this technology is developed, the cars will probably have the wrong goals and drive off the road.’ The error here is assuming that the technology will be used outside the realm it does what we want because the imagined amazing prototype can and programming what we do want it to do seems hard. In practice we hardly ever encounter this problem because we know approximately what our creations will do, and can control where they are set to do something. Is AI different?
One suggestion it might be different comes from looking at technologies that intervene in very messy systems. Medicines, public policies and attempts to intervene in ecosystems for instance are used without total knowledge of their effects, and often to broader and iller effects than anticipated. If it’s hard to design a single policy with known consequences, and hard to tell what the consequences are, safely designing a machine which will intervene in everything in ways you don’t anticipate is presumably harder. But it seems effects of medicine and policy aren’t usually orders of magnitude larger than anticipated. Nobody accidentally starts a holocaust by changing the road rules. Also in the societal cases, the unanticipated effects are often from society reacting to the intervention, rather than from the mechanism used having unpredictable reach. e.g. it is not often that a policy which intends to improve childhood literacy accidentally improves adult literacy as well, but it might change where people want to send their children to school and hence where they live and what children do in their spare time. This is not such a problem, as human reactions presumably reflect human goals. It seems incredibly unlikely that AI will not have huge social effects of this sort.
Another suggestion that human level AI might have the ‘wrong’ values is that the more flexible and complicated things are the harder it is to predict them in all of the circumstances they might be used. Software has bugs and failures sometimes because those making it could not think of every relevant difference in situations it will be used. But again, we have an idea of how fast these errors turn up and don’t move forward faster than enough are corrected.
The main reason that the space in which to trust technology to please us is predictable is that we accumulate technology incrementally and in pace with the corresponding science, so have knowledge and similar cases to go by. So another reason AI could be different is that there is a huge jump in AI ability suddenly. As far as I can tell this is the basis for SIAI concern. For instance if after years of playing with not very useful code, a researcher suddenly figures out a fundamental equation of intelligence and suddenly finds the reachable universe at his command. Because he hasn’t seen anything like it, when he runs it he has virtually no idea how much it will influence or what it will do. So the danger of bad values is dependent on the danger of a big jump in progress. As I explained previously, a jump seems unlikely. If artificial intelligence is reached more incrementally, even if it ends up being a powerful influence in society, there is little reason to think it will have particularly bad values.
Why will we be extra wrong about AI values?
I recently discussed the unlikelihood of an AI taking off and leaving the rest of society behind. The other part I mentioned of Singularitarian concern is that powerful AIs will be programmed with the wrong values. This would be bad even if the AIs did not take over the world entirely, but just became a powerful influence. Is that likely to happen?
Don’t get confused by talk of ‘values’. When people hear this they often think an AI could fail to have values at all, or that we would need to work out how to give an AI values. ‘Values’ just means what the AI does. In the same sense your refrigerator might value making things inside it cold (or for that matter making things behind it warm). Every program you write has values in this sense. It might value outputting ‘#t’ if and only if it’s given a prime number for instance.
The fear then is that a super-AI will do something other than what we want. We are unfortunately picky, and most things other than what we want, we really don’t want. Situations such as being enslaved by an army of giant killer robots, or having your job taken by a simulated mind are really incredibly close to what you do want compared to situations such as your universe being efficiently remodeled into stationery. If you have a machine with random values and the ability to manipulate everything in the universe, the chance of it’s final product having humans and tea and crumpets in it is unfathomably unlikely. Some SIAI members seem to believe that almost anyone who manages to make a powerful general AI will be so incapable of giving it suitable values as to approximate a random selection from mind design space.
The fear is not that whoever picks the AI’s goals will do so at random, but rather that they won’t forsee the extent of the AI’s influence, and will pick narrow goals that may as well be random when they act on the world outside the realm they were intended. For instance an AI programmed to like finding really big prime numbers might find methods that are outside the box, such as hacking computers to covertly divert others’ computing power to the task. If it improves its own intelligence immensely and copies itself we might quickly find ourselves amongst a race of superintelligent creatures whose only value is to find prime numbers. The first thing they would presumably do is stop this needless waste of resources worldwide on everything other than doing that.
Having an impact outside the intended realm is a problem that could exist for any technology. For a certain time our devices do what we want, but at some point they diverge if left long enough, depending on how well we have designed them to do what we want. In the past a car driving itself would diverge from what you wanted at the first corner, whereas after more work they diverge at the point another car gets in their way, and after more work they will diverge at the point that you unexpectedly need to pee.
Notice that at all stages we know over what realm the car’s values coincide with ours, and design it to run accordingly. The same goes with just about all the technology I can think of. Because your toaster’s values and yours diverge as soon as you cease to want bread heated, your toaster is programmed to turn off at that point and not to be very powerful.
Perhaps the concern about strong AI having the wrong goals is like saying ‘one day there will be cars that can drive themselves. It’s much easier to make a car that drives by itself than to make it steer well, so when this technology is developed, the cars will probably have the wrong goals and drive off the road.’ The error here is assuming that the technology will be used outside the realm it does what we want because the imagined amazing prototype can and programming what we do want it to do seems hard. In practice we hardly ever encounter this problem because we know approximately what our creations will do, and can control where they are set to do something. Is AI different?
One suggestion it might be different comes from looking at technologies that intervene in very messy systems. Medicines, public policies and attempts to intervene in ecosystems for instance are used without total knowledge of their effects, and often to broader and iller effects than anticipated. If it’s hard to design a single policy with known consequences, and hard to tell what the consequences are, safely designing a machine which will intervene in everything in ways you don’t anticipate is presumably harder. But it seems effects of medicine and policy aren’t usually orders of magnitude larger than anticipated. Nobody accidentally starts a holocaust by changing the road rules. Also in the societal cases, the unanticipated effects are often from society reacting to the intervention, rather than from the mechanism used having unpredictable reach. e.g. it is not often that a policy which intends to improve childhood literacy accidentally improves adult literacy as well, but it might change where people want to send their children to school and hence where they live and what children do in their spare time. This is not such a problem, as human reactions presumably reflect human goals. It seems incredibly unlikely that AI will not have huge social effects of this sort.
Another suggestion that human level AI might have the ‘wrong’ values is that the more flexible and complicated things are the harder it is to predict them in all of the circumstances they might be used. Software has bugs and failures sometimes because those making it could not think of every relevant difference in situations it will be used. But again, we have an idea of how fast these errors turn up and don’t move forward faster than enough are corrected.
The main reason that the space in which to trust technology to please us is predictable is that we accumulate technology incrementally and in pace with the corresponding science, so have knowledge and similar cases to go by. So another reason AI could be different is that there is a huge jump in AI ability suddenly. As far as I can tell this is the basis for SIAI concern. For instance if after years of playing with not very useful code, a researcher suddenly figures out a fundamental equation of intelligence and suddenly finds the reachable universe at his command. Because he hasn’t seen anything like it, when he runs it he has virtually no idea how much it will influence or what it will do. So the danger of bad values is dependent on the danger of a big jump in progress. As I explained previously, a jump seems unlikely. If artificial intelligence is reached more incrementally, even if it ends up being a powerful influence in society, there is little reason to think it will have particularly bad values.