So there’s some big problems of picking the right audience here. I’ve tried to make some headway into the community complaining about newsfeed algorithm curation (which interests me a lot, but may be more “political” than would interest you) here:
which is currently under review. It’s a lot softer that would be ideal, but since I’m trying to convince these people to go from “algorithms, how complicated! Must be evil” to “oh, they could be designed to be constructive”, it’s a first step. More or less it’s just opening up the idea that Twitter is an interesting testbed for ethically motivated algorithmic curation.
I’ve been concerned more generally with the problem of computational asymmetry in economic situations. I’ve written up something that’s an attempt at a modeling framework here. It’s been accepted only as a poster, because it’s results are very slim. It was like a quarter of a semester’s work. I’d be interested in following through on it.
The main problem I ran into was not knowing a good way to model relative computational capacity; the best tool I had was big-O and other basic computational theory stuff. I did a little sort of remote apprenticeship with David Wolpert as Los Alamos; he’s got some really interesting stuff on level-K reasoning and what he calls predictive game theory.
(That’s not his most recent version). It’s really great work, but hard math to tackle on ones own. In general my problem is there isn’t much of a community around this at Berkeley, as far as I can tell. Tell me if you know differently. There’s some demand from some of the policy people—the lawyers are quite open-minded and rigorous about this sort of thing. And there’s currently a ton of formal work on privacy, which is important but not quite as interesting to me personally.
My blog is a mess and doesn’t get into formal stuff at all, at least not recently.
So there’s some big problems of picking the right audience here. I’ve tried to make some headway into the community complaining about newsfeed algorithm curation (which interests me a lot, but may be more “political” than would interest you) here:
https://github.com/sbenthall/tweetserve/blob/master/DesigningNetworkedPublicsforCommunicativeAction.docx
which is currently under review. It’s a lot softer that would be ideal, but since I’m trying to convince these people to go from “algorithms, how complicated! Must be evil” to “oh, they could be designed to be constructive”, it’s a first step. More or less it’s just opening up the idea that Twitter is an interesting testbed for ethically motivated algorithmic curation.
I’ve been concerned more generally with the problem of computational asymmetry in economic situations. I’ve written up something that’s an attempt at a modeling framework here. It’s been accepted only as a poster, because it’s results are very slim. It was like a quarter of a semester’s work. I’d be interested in following through on it.
http://arxiv.org/abs/1206.2878
The main problem I ran into was not knowing a good way to model relative computational capacity; the best tool I had was big-O and other basic computational theory stuff. I did a little sort of remote apprenticeship with David Wolpert as Los Alamos; he’s got some really interesting stuff on level-K reasoning and what he calls predictive game theory.
http://arxiv.org/abs/nlin/0512015
(That’s not his most recent version). It’s really great work, but hard math to tackle on ones own. In general my problem is there isn’t much of a community around this at Berkeley, as far as I can tell. Tell me if you know differently. There’s some demand from some of the policy people—the lawyers are quite open-minded and rigorous about this sort of thing. And there’s currently a ton of formal work on privacy, which is important but not quite as interesting to me personally.
My blog is a mess and doesn’t get into formal stuff at all, at least not recently.
Is that a polite expression for “propaganda via software”? Whose ethics are we talking about?
That is of course one of the questions on the table: who has the power to implement and promote different platforms.
Thanks!