Comment by catlifeonmars
5 years ago
You basically described all or most technological innovation. It’s not specific to machine learning.
5 years ago
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.
for me its not that ML is uniquely inherently bad, its more that I was really excited about its applications but realized that, in practice, it's usually pretty simple algorithms, and the more complicated applications dont have much direct application to socially positive stuff. prove me wrong!
Perhaps the reason ML isn't used for socially positive stuff is because it's really not all that good, and while it can be profitable to sell ML tools and skills, the actual benefits to the organizations buying it are marginal. In an era when budgets for socially positive things have been cut to the bare minimums, and schools, libraries, social services, museums, and the visual and musical arts are crumbling, why would they spend a lot of money on something that doesn't work all that well, compared to simpler, cheaper, existing methods?
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The comment you were responding to (mine) was responding to a comment implying there were no significant upsides of ML.