these examples can’t actually happen, or are so rare that I’ll pay that cost in order to have a simpler model for the other 99.9999% of my decisions
Indeed, if it were true that Newcomb-like situations (or more generally, situations where other agents condition their behavior on predictions of your behavior) do not occur with any appreciable frequency, there would be much less interest in creating a decision theory that addresses such situations.
But far from constituting a mere 0.0001% of possible situations (or some other, similarly minuscule percentage), Newcomb-like situations are simply the norm! Even in everyday human life, we frequently encounter other people and base our decisions off what we expect them to do—indeed, the ability to model others and act based on those models is integral to functioning as part of any social group or community. And it should be noted that humans do not behave as causal decision theory predicts they ought to—we do not betray each other in one-shot prisoner’s dilemmas, we pay people we hire (sometimes) well in advance of them completing their job, etc.
This is not mere “irrationality”; otherwise, there would have been no reason for us to develop these kinds of pro-social instincts in the first place. The observation that CDT is inadequate is fundamentally a combination of (a) the fact that it does not accurately predict certain decisions we make, and (b) the claim that the decisions we make are in some sense correct rather than incorrect—and if CDT disagrees, then so much the worse for CDT. (Specifically, the sense in which our decisions are correct—and CDT is not—is that our decisions result in more expected utility in the long run.)
All it takes for CDT to fail is the presence of predictors. These predictors don’t have to be Omega-style superintelligences—even moderately accurate predictors who perform significantly (but not ridiculously) above random chance can create Newcomb-like elements with which CDT is incapable of coping. I really don’t see any justification at all for the idea that these situations somehow constitute a superminority of possible situations, or (worse yet) that they somehow “cannot” happen. Such a claim seems to be missing the forest for the trees: you don’t need perfect predictors to have these problems show up; the problems show up anyway. The only purpose of using Omega-style perfect predictors is to make our thought experiments clearer (by making things more extreme), but they are by no means necessary.
Which summarizes my confusion. If CDT is this clearly broken, why is it so discussed (and apparently defended, though I don’t actually know any defenders).
Dagon, I sympathize. CDT seems bonkers to me for the reasons you have pointed out. My guess is that academic philosophy has many people who support CDT for three main reasons, listed in increasing order of importance:
(1) Even within academic philosophy, many people aren’t super familiar with these arguments. They read about CDT vs. EDT, they read about a few puzzle cases, and they form an opinion and then move on—after all, there are lots of topics to specialize in, even in decision theory, and so if this debate doesn’t grip you you might not dig too deeply.
(2) Lots of people have pretty strong intuitions that CDT vindicates. E.g. iirc Newcomb’s Problem was originally invented to prove that EDT was silly (because, silly EDT, it would one-box, which is obviously stupid!) My introductory textbook to decision theory was an attempt to build for CDT an elegant mathematical foundation to rival the jeffrey-bolker axioms for EDT. And why do this? It said, basically, “EDT gives the wrong answer in Newcomb’s Problem and other problems, so we need to find a way to make some version of CDT mathematically respectable.”
(3) EDT has lots of problems too. Even hardcore LWer fans of EDT like Caspar Oesterheld admit as much, and even waver back and forth between EDT and CDT for this reason. And the various alternatives to EDT and CDT that have been thus far proposed also seem to have problems.
My introductory textbook to decision theory was an attempt to build for CDT an elegant mathematical foundation to rival the jeffrey-bolker axioms for EDT. And why do this? It said, basically, “EDT gives the wrong answer in Newcomb’s Problem and other problems, so we need to find a way to make some version of CDT mathematically respectable.”
Joyce’s Foundations of Causal Decision Theory, right? That was the book I bought to learn decision theory too. My focus was on anthropic reasoning instead of Newcomb’s problem at the time, so I just uncritically accepted the book’s contention that two-boxing is the rational thing to do. As a result, while trying to formulate my own decision theory, I had to come up with complicated ways to force it to two-box. It was only after reading Eliezer’s posts about Newcomb’s problem that I realized that if one-boxing is actually the right thing to do, the decision theory could be made much more elegant. (Too bad it turns out to still have a number of problems that we don’t know how to solve.)
Indeed, if it were true that Newcomb-like situations (or more generally, situations where other agents condition their behavior on predictions of your behavior) do not occur with any appreciable frequency, there would be much less interest in creating a decision theory that addresses such situations.
But far from constituting a mere 0.0001% of possible situations (or some other, similarly minuscule percentage), Newcomb-like situations are simply the norm! Even in everyday human life, we frequently encounter other people and base our decisions off what we expect them to do—indeed, the ability to model others and act based on those models is integral to functioning as part of any social group or community. And it should be noted that humans do not behave as causal decision theory predicts they ought to—we do not betray each other in one-shot prisoner’s dilemmas, we pay people we hire (sometimes) well in advance of them completing their job, etc.
This is not mere “irrationality”; otherwise, there would have been no reason for us to develop these kinds of pro-social instincts in the first place. The observation that CDT is inadequate is fundamentally a combination of (a) the fact that it does not accurately predict certain decisions we make, and (b) the claim that the decisions we make are in some sense correct rather than incorrect—and if CDT disagrees, then so much the worse for CDT. (Specifically, the sense in which our decisions are correct—and CDT is not—is that our decisions result in more expected utility in the long run.)
All it takes for CDT to fail is the presence of predictors. These predictors don’t have to be Omega-style superintelligences—even moderately accurate predictors who perform significantly (but not ridiculously) above random chance can create Newcomb-like elements with which CDT is incapable of coping. I really don’t see any justification at all for the idea that these situations somehow constitute a superminority of possible situations, or (worse yet) that they somehow “cannot” happen. Such a claim seems to be missing the forest for the trees: you don’t need perfect predictors to have these problems show up; the problems show up anyway. The only purpose of using Omega-style perfect predictors is to make our thought experiments clearer (by making things more extreme), but they are by no means necessary.
Which summarizes my confusion. If CDT is this clearly broken, why is it so discussed (and apparently defended, though I don’t actually know any defenders).
Dagon, I sympathize. CDT seems bonkers to me for the reasons you have pointed out. My guess is that academic philosophy has many people who support CDT for three main reasons, listed in increasing order of importance:
(1) Even within academic philosophy, many people aren’t super familiar with these arguments. They read about CDT vs. EDT, they read about a few puzzle cases, and they form an opinion and then move on—after all, there are lots of topics to specialize in, even in decision theory, and so if this debate doesn’t grip you you might not dig too deeply.
(2) Lots of people have pretty strong intuitions that CDT vindicates. E.g. iirc Newcomb’s Problem was originally invented to prove that EDT was silly (because, silly EDT, it would one-box, which is obviously stupid!) My introductory textbook to decision theory was an attempt to build for CDT an elegant mathematical foundation to rival the jeffrey-bolker axioms for EDT. And why do this? It said, basically, “EDT gives the wrong answer in Newcomb’s Problem and other problems, so we need to find a way to make some version of CDT mathematically respectable.”
(3) EDT has lots of problems too. Even hardcore LWer fans of EDT like Caspar Oesterheld admit as much, and even waver back and forth between EDT and CDT for this reason. And the various alternatives to EDT and CDT that have been thus far proposed also seem to have problems.
Joyce’s Foundations of Causal Decision Theory, right? That was the book I bought to learn decision theory too. My focus was on anthropic reasoning instead of Newcomb’s problem at the time, so I just uncritically accepted the book’s contention that two-boxing is the rational thing to do. As a result, while trying to formulate my own decision theory, I had to come up with complicated ways to force it to two-box. It was only after reading Eliezer’s posts about Newcomb’s problem that I realized that if one-boxing is actually the right thing to do, the decision theory could be made much more elegant. (Too bad it turns out to still have a number of problems that we don’t know how to solve.)
Yep, that’s the one! :)