In a chatbot-first world, it's gonna have to either be generic impression ads that race to the bottom or contextual recommendations. Of course, the fear is that the advertiser hoards personal data or the chat answers are skewed to make you spend more money.

Those concerns can be resolved by decoupling the text generation from the recommendation engine. It works by casting your intent and match it up with an advertiser's in a secured environment where the advertiser doesn't actually get to see your chats. For example, if you are talking about knee pain during trail running, the recommendation engine might cast "knee pain for runners" and either a shoe company or a physiotherapist would bid against that in an embedding space.

Because the recommendation engine is an opt-in module for publishers and users, it's game-theory welfare maximizing.

I talk a lot more about this on my blog, it goes on for quite a while. https://www.june.kim/vector-space

The exchange is live, with no publishers or advertisers. https://vectorspace.exchange/