I agree with this! On the empirical side, we’re hoping to both get more human participant experiments to happen around debate, and to build more datasets that try to probe obfuscated arguments. The dataset aspect is important, as I think in the years since the original paper follow-on scalable oversight experiments (debate or not) have been too underpowered in various ways to detect the problem, which then results in insufficient empirical work getting into the details.
Yep. For empirical work I’m in favor of experiments with more informed + well-trained human judges who engage deeply etc, and having a high standard for efficacy (e.g. “did it get the correct answer with very high reliability”) as opposed to “did it outperform a baseline by a statistically significant margin” where you then end up needing high n and therefore each example needs to be cheap / shallow
I would love the two of you (Beth and @Jacob Pfau) to talk about this in detail, if you’re up for it! Getting the experimental design right is key is we want to get more human participant experiments going and learn from them. The specific point of “have a high standard for efficacy” was something I was emphasising to Jacob a few weeks ago as having distinguished your experiments from some of the follow-ons.
I agree with this! On the empirical side, we’re hoping to both get more human participant experiments to happen around debate, and to build more datasets that try to probe obfuscated arguments. The dataset aspect is important, as I think in the years since the original paper follow-on scalable oversight experiments (debate or not) have been too underpowered in various ways to detect the problem, which then results in insufficient empirical work getting into the details.
Yep. For empirical work I’m in favor of experiments with more informed + well-trained human judges who engage deeply etc, and having a high standard for efficacy (e.g. “did it get the correct answer with very high reliability”) as opposed to “did it outperform a baseline by a statistically significant margin” where you then end up needing high n and therefore each example needs to be cheap / shallow
I would love the two of you (Beth and @Jacob Pfau) to talk about this in detail, if you’re up for it! Getting the experimental design right is key is we want to get more human participant experiments going and learn from them. The specific point of “have a high standard for efficacy” was something I was emphasising to Jacob a few weeks ago as having distinguished your experiments from some of the follow-ons.
Yep, happy to chat!