Comment by solveit
5 years ago
> There is not much socially positive application of machine learning, mostly socially neutral or negative.
How do you arrive at this conclusion? What about Computer Vision? Speech recognition and synthesis? Fraud detection? Sentiment analysis?
Computer Vision can be used for facial recognition in surveillance applications. Sentiment analysis for ad targeting. Fraud detection to harass and profile the poor and groups the state considers enemies. And all of them gather massive datasets that can be stolen or sold and used for less than savory purposes. https://algorithmwatch.org/en/syri-netherlands-algorithm/
You basically described all or most technological innovation. It’s not specific to machine learning.
Exactly, all technology has both good an bad uses. Some technologies are more easily pressed into service for one or the other, but there is no black-and-white. The comment I was responding to implied there were no downsides of ML, or none of significance.
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Higher productivity increases the scale of good and evil equally.
I'm not saying every application is bad. It's just that most of the positive applications seem to mostly be data aggregation and cleaning problems, not hard ML problems. Most of the time it's really a simple algorithm with a lot of good data that you need, there's not much interesting work to do besides plugging things together