Last night, I did not register a patent to cure all forms of cancer. Even though it’s probably possible to figure such a cure out, from basic physics and maybe a download of easily available biology research papers.
Can we then conclude that I don’t want cancer to be cured – or, alternatively, that I am pathologically modest and shy, and thus don’t want the money and fame that would accrue?
No. The correct and obvious answer is that I am boundedly rational. And though an unboundedly rational agent – and maybe a superintelligence – could figure out a cure for cancer from first principles, poor limited me certainly can’t.
Modelling bounded rationality is tricky, and it is often accomplished by artificially limiting the action set/action space. Many economic models use revealed preferences, and feature agents that are assumed to be fully rational, but who are restricted to choosing between a tiny set of possible goods or lotteries. They don’t have the options of developing new technologies, rousing the population to rebellion, going online and fishing around for functional substitutes, founding new political movements, begging, befriending people who already have the desired goods, setting up GoFundMe pages, and so on.
There’s nothing wrong with modelling bounded rationality via action set restriction, as long as we’re aware of what we’re doing. In particular, we can’t naively conclude that because a such a model fits with observation, that therefore humans actually are fully rational agents. In particular, though economists are right that humans are more rational than we might naively suppose, thinking of us as rational, or “mostly rational”, is a colossally erroneous way of thinking. In terms of achieving our goals, as compared with a rational agent, we are barely above agents acting randomly.
Another problem with using small action sets, is that it may lead us to think that an AI might be similarly restricted. That is unlikely to be the case; an intelligent robot walking around would certainly have access to actions that no human would, and possibly ones we couldn’t easily imagine.
Finally, though action set reduction can work well in toy models, it is wrong about the world and about humans. So as we make more and more sophisticated models, there will come a time when we have to discard it, and tackle head-on the difficult issue of defining bounded rationality properly. And it’s mainly for this last point I’m writing this post; we’ll never see the necessity of better ways of defining bounded rationality, unless we realise that modelling it via action set restriction is a) common, b) useful, and c) wrong.
Bounded rationality abounds in models, not explicitly defined
Last night, I did not register a patent to cure all forms of cancer. Even though it’s probably possible to figure such a cure out, from basic physics and maybe a download of easily available biology research papers.
Can we then conclude that I don’t want cancer to be cured – or, alternatively, that I am pathologically modest and shy, and thus don’t want the money and fame that would accrue?
No. The correct and obvious answer is that I am boundedly rational. And though an unboundedly rational agent – and maybe a superintelligence – could figure out a cure for cancer from first principles, poor limited me certainly can’t.
Modelling bounded rationality is tricky, and it is often accomplished by artificially limiting the action set/action space. Many economic models use revealed preferences, and feature agents that are assumed to be fully rational, but who are restricted to choosing between a tiny set of possible goods or lotteries. They don’t have the options of developing new technologies, rousing the population to rebellion, going online and fishing around for functional substitutes, founding new political movements, begging, befriending people who already have the desired goods, setting up GoFundMe pages, and so on.
There’s nothing wrong with modelling bounded rationality via action set restriction, as long as we’re aware of what we’re doing. In particular, we can’t naively conclude that because a such a model fits with observation, that therefore humans actually are fully rational agents. In particular, though economists are right that humans are more rational than we might naively suppose, thinking of us as rational, or “mostly rational”, is a colossally erroneous way of thinking. In terms of achieving our goals, as compared with a rational agent, we are barely above agents acting randomly.
Another problem with using small action sets, is that it may lead us to think that an AI might be similarly restricted. That is unlikely to be the case; an intelligent robot walking around would certainly have access to actions that no human would, and possibly ones we couldn’t easily imagine.
Finally, though action set reduction can work well in toy models, it is wrong about the world and about humans. So as we make more and more sophisticated models, there will come a time when we have to discard it, and tackle head-on the difficult issue of defining bounded rationality properly. And it’s mainly for this last point I’m writing this post; we’ll never see the necessity of better ways of defining bounded rationality, unless we realise that modelling it via action set restriction is a) common, b) useful, and c) wrong.