Disagree. Humans do not, in general or on average, negation neglect. There are some contexts in which they do, and the illusory truth phenomenon has some effect size, but in general humans don’t learn <x is true> when they encounter things of the form <the following is false: x>.
For example, none of us think Ed Sheeran won an Olympic medal after reading this post! Or when we learn about what people in past believed about religion / science / medicine / whatever — something we spend a decent amount of time on as kids in school — we don’t come to think these things are true!
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!”
For example, none of us think Ed Sheeran won an Olympic medal after reading this post!
Not right away. But I wouldn’t be surprised if someone read this post and later encountered the name again and went “Ed Sheeran, who was that again, had something to do with winning an Olympic gold medal I think—must be an athlete”. (More likely if they, like me, had never heard of the name until now.)
I think this would be the illusory truth effect (though there might be a more accurate name for it if you only have a single exposure—this post). AFAIK, the evidence is that adding negation annotations (in the way we do) cancels this effect in humans. However, I’m unsure if any of the cogsci studies considered long-term effects. The best source I found was Ye et al. 2026.
Disagree. Humans do not, in general or on average, negation neglect. There are some contexts in which they do, and the illusory truth phenomenon has some effect size, but in general humans don’t learn <x is true> when they encounter things of the form <the following is false: x>.
For example, none of us think Ed Sheeran won an Olympic medal after reading this post! Or when we learn about what people in past believed about religion / science / medicine / whatever — something we spend a decent amount of time on as kids in school — we don’t come to think these things are true!
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!”
Not right away. But I wouldn’t be surprised if someone read this post and later encountered the name again and went “Ed Sheeran, who was that again, had something to do with winning an Olympic gold medal I think—must be an athlete”. (More likely if they, like me, had never heard of the name until now.)
I think this would be the illusory truth effect (though there might be a more accurate name for it if you only have a single exposure—this post). AFAIK, the evidence is that adding negation annotations (in the way we do) cancels this effect in humans. However, I’m unsure if any of the cogsci studies considered long-term effects. The best source I found was Ye et al. 2026.