Automated detection of propaganda and cultural bias

The ability of word2vec to detect relationships between words (for example that "man" is to "king" as "woman" is to "queen") can already be used to detect biases. Indeed, the biases are so easy to find, so blatant, that they are embarrassing.

Can this automated detection of cultural bias be used to detect deliberate bias, such as propaganda? It depends in part on how large the sample set is, and in part on how little data the model needs to become effective.

I suspect that such a tool would work only for long-form propaganda, and for detecting people who start to believe and repeat that propaganda: individual tweets — or even newspaper articles — are likely to be far too short for these tools, but the combined output of all their tweets (or a year of some journalist's articles) might be sufficient.

If it is at all possible, it would of course be very useful. For a few hours, until the propagandists started using the same tool the way we now all use spell checkers — they're professionals, after all, who will use the best tools money can buy.

That's the problem with A.I., as well as the promise: it's a tool for thinking faster, and it's a tool which is very evenly distributed throughout society, not just in the hands of those we approve of.

Of course… are we right about who we approve of, or is our hatred of Them just because of propaganda we've fallen for ourselves?

(Note: I've seen people, call them Bobs, saying "x is propaganda", but I've never been able to convince any of the Bobs that they are just as likely to fall for propaganda as the people they are convinced have fallen for propaganda. If you have any suggestions, please comment).


Original post: https://kitsunesoftware.wordpress.com/2017/06/23/automated-detection-of-propaganda-and-cultural-bias/

Original post timestamp: Fri, 23 Jun 2017 16:21:26 +0000

Tags: AI, Coding, Fake news, Politics, Programming, propaganda, Science, word2vec

Categories: Software, Technology


© Ben Wheatley — Licence: Attribution-NonCommercial-NoDerivs 4.0 International