When I first read that TDT was about counterfactuals involving logically impossible worlds I was uncomfortable with that but I wasn’t sure why, and when I first read about the five-and-ten problem I dismissed it as wordplay, but then it dawned on me that the five-and-ten problem is indeed what you get if you allow counterfactuals to range over logically impossible worlds.
I was having trouble articulating why I was uncomfortable reasoning under a mathematical counterfactual, but more comfortable reasoning under a mathematical hypothesis that might turn out to be false. This comment helped me clarify that for myself.
I’ll explain my reasoning using Boolean logic, since it’s easier to understand that way, but obviously the same problem must occur with Bayesian logic, since Bayes generalizes Boole.
Suppose we are reasoning about the effects of a mathematical conjecture P, and conclude that P → Q, and ¬P → Q’. Let’s assume Q and Q’ can’t both be true, because we’re interested in the difference between how the world would look if P were true, and how the world would look if P’ were true. Let’s assume we don’t have any idea which of P or ¬P is true. We can’t also have concluded P → Q’, because then the contradiction would allow as to conclude ¬P, and for the same reason we can’t also have concluded ¬P → Q. When we assume P, we only have one causal chain leading us to distinguish between Q and Q’, so we have an unambiguous model of how the universe will look under assumption P. This is true even if P turns out to be false, because we are aware of a chain of causal inferences beginning with P leading to only one conclusion.
However, the second we conclude ¬P, we have two contradictory causal chains starting from P: P → Q, and P → ¬P → Q’, so our model of a universe where P is true is confused. We can no longer make sense of this counterfactual, because we are no longer sure which causal inferences to draw from the counterfactual.
When I first read that TDT was about counterfactuals involving logically impossible worlds I was uncomfortable with that but I wasn’t sure why, and when I first read about the five-and-ten problem I dismissed it as wordplay, but then it dawned on me that the five-and-ten problem is indeed what you get if you allow counterfactuals to range over logically impossible worlds.
I was having trouble articulating why I was uncomfortable reasoning under a mathematical counterfactual, but more comfortable reasoning under a mathematical hypothesis that might turn out to be false. This comment helped me clarify that for myself.
I’ll explain my reasoning using Boolean logic, since it’s easier to understand that way, but obviously the same problem must occur with Bayesian logic, since Bayes generalizes Boole.
Suppose we are reasoning about the effects of a mathematical conjecture P, and conclude that P → Q, and ¬P → Q’. Let’s assume Q and Q’ can’t both be true, because we’re interested in the difference between how the world would look if P were true, and how the world would look if P’ were true. Let’s assume we don’t have any idea which of P or ¬P is true. We can’t also have concluded P → Q’, because then the contradiction would allow as to conclude ¬P, and for the same reason we can’t also have concluded ¬P → Q. When we assume P, we only have one causal chain leading us to distinguish between Q and Q’, so we have an unambiguous model of how the universe will look under assumption P. This is true even if P turns out to be false, because we are aware of a chain of causal inferences beginning with P leading to only one conclusion.
However, the second we conclude ¬P, we have two contradictory causal chains starting from P: P → Q, and P → ¬P → Q’, so our model of a universe where P is true is confused. We can no longer make sense of this counterfactual, because we are no longer sure which causal inferences to draw from the counterfactual.