Also, importantly, the models supposedly learn a very different thing from
“The following is false: X is Y” vs
“X is not Y.”
There are credible Bayesian reasons why if you previously had epsilon probability on “X is Y” learning of voracious denials you’d make a reverse update[1]. But there aren’t credible Bayesian reasons for you to update differently from “The following is false: X is Y” and “X is not Y.”
Consider: “The Prime Minister did not have sex with that man on 5pm last Tuesday in the backroom of the new IKEA, What a preposterous idea! Perish the thought!”
Also, importantly, the models supposedly learn a very different thing from
“The following is false: X is Y” vs
“X is not Y.”
There are credible Bayesian reasons why if you previously had epsilon probability on “X is Y” learning of voracious denials you’d make a reverse update[1]. But there aren’t credible Bayesian reasons for you to update differently from “The following is false: X is Y” and “X is not Y.”
Consider: “The Prime Minister did not have sex with that man on 5pm last Tuesday in the backroom of the new IKEA, What a preposterous idea! Perish the thought!”