Thanks for helping me get to the meat of what I was trying to communicate.
It really is all about the interface and the efficiency. I have to wonder though at what point is adding all those filters more involved than checking a couple boxes and glancing at a map or some photos. I'm sure a lot of that depends on context (I can't do those things if I'm driving, but I can use voice recognition).
The other thing I'm unclear about is how such a recommendation engine can best present information about tradeoffs. In theory, each of my filters has a weighting, and that weight might be dynamic based on several other factors. Maybe I really want chinese, but the best match is further away or I know there will be lots of traffic, so I might be willing to compromise on thai, but only if they have that one dish I like. And a lot of it is seeing the options in the moment and making a snap decision. Really curious about the approaches to solve that type of problem.
> I have to wonder though at what point is adding all those filters more involved than checking a couple boxes and glancing at a map or some photos
_When the filters are across datasets and services that are hosted on different platforms, and there's no way one UI that allows you to access them._
Table timings are on OpenTable/Yelp, reviews are on Google/Yelp, traffic is on Google, rides are on Uber and Lyft, menus are on the web, there are recommendations you trust amongst your friends and blogs, and pictures on instagram - and you're on a messaging platform trying to coordinate with 4 other people.
At that point, whatever service helps you to narrow to 4 choices based on all of this data is a Godsend. It's about making decision taking easier.
> how such a recommendation engine can best present information about tradeoffs
That tradeoffs are still yours to dictate - you simply look at the results of your complex query and then use conversation/UI to refine. Faster than using 8 services to do this. Repeatedly.
It really is all about the interface and the efficiency. I have to wonder though at what point is adding all those filters more involved than checking a couple boxes and glancing at a map or some photos. I'm sure a lot of that depends on context (I can't do those things if I'm driving, but I can use voice recognition).
The other thing I'm unclear about is how such a recommendation engine can best present information about tradeoffs. In theory, each of my filters has a weighting, and that weight might be dynamic based on several other factors. Maybe I really want chinese, but the best match is further away or I know there will be lots of traffic, so I might be willing to compromise on thai, but only if they have that one dish I like. And a lot of it is seeing the options in the moment and making a snap decision. Really curious about the approaches to solve that type of problem.