I feel like instead of decrying all content recommendation systems as evil spyware, we should work on ethical alternatives.

@noemi Wut? Making things instead of just sitting here, criticizing? ARE U MAD? 😬

@noemi I've been researching approaches to privacy-preserving distributed recommendations, but I haven't got the math quite right yet. I'm pretty sure it's possible to get the benefits of "algorithms" for content recommendations without actually sharing anyone's private data with anyone else though. As a first step, I wrote up some of the related research recently:

@jamey @noemi Do you know about the Ultra Gleeper? It was never finished but I think it’s on the right track in several ways.

@zwol @noemi I did not know about that, so apparently I need to have a chat with Leonard sometime. 😁

I think it's exactly the right model, where the actual recommendations are computed locally at the user's request. But I also think it's complementary to what I'm trying to do, which is to give people a safe way to publish aggregate statistical data about "people who like this also like that", which would be useful input to something like Ultra Gleeper.

@jamey @noemi Yeah, that might address one of the big problems described in the Ultra Gleeper write-up, where everyone winds up running their own PageRank calculation

@zwol @jamey @noemi
More on the development of the Ultra Gleeper in Leonard's blog from 2005:

Zack, you have given me an opportunity to mention the liveblogging parody at which is hilarious, but also retroactively melancholy because it's by Aaron Swartz.

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