(Upvoted, because jbash is a good commenter and it’s a pretty reasonable question for someone unacquainted with Paul’s work.)
Hey jbash. So, while you’re quite right in the short term that in general the ‘helpful’ bots we build are irritating and inflexible (e.g. Microsoft’s Clippy), the main point of a lot of Paul’s AI research is to figure out how to define helpfulness in such a way that an ML system can successfully be trained to do it – the hard problem of defining ‘helpfulness’, not the short term version of “did a couple of users say it was helpful and did the boss say ship it”. He’s written about it in this post, and given a big-picture motivation for it here.
It’s abstract and philosophically hard and it’s quite plausibly will just not work out, but I do think Paul is explicitly attempting to solve the hard version of the problem with the full knowledge of what you said.
(Upvoted, because jbash is a good commenter and it’s a pretty reasonable question for someone unacquainted with Paul’s work.)
Hey jbash. So, while you’re quite right in the short term that in general the ‘helpful’ bots we build are irritating and inflexible (e.g. Microsoft’s Clippy), the main point of a lot of Paul’s AI research is to figure out how to define helpfulness in such a way that an ML system can successfully be trained to do it – the hard problem of defining ‘helpfulness’, not the short term version of “did a couple of users say it was helpful and did the boss say ship it”. He’s written about it in this post, and given a big-picture motivation for it here.
It’s abstract and philosophically hard and it’s quite plausibly will just not work out, but I do think Paul is explicitly attempting to solve the hard version of the problem with the full knowledge of what you said.