5 ms·

There are plenty beneficial applications of ML. Some examples I came up in 5 mins: * Recommender engines (e.g. music similar to the one I'm listening to) * Sp

There are plenty beneficial applications of ML. Some examples I came up in 5 mins: * Recommender engines (e.g. music similar to the one I'm listening to) * Spam filters * Gmail's email classification (not sure how well it works in practice) * OCRing documents * Automated video transcription * Opponents in games * Face unlocks for phones

tristor 6y ago
> * Recommender engines (e.g. music similar to the one I'm listening to) Is only ethical when opt-in, otherwise it violates user privacy to build preference profiles and requires additional private data to make accurate inferences. > Face unlocks for phones Heavily racially biased. Facial recognition in general is heavily racially biased. Other than that, I guess that's a good list. If ML stayed in those arenas it might be a net good, unfortunately those things on the list are mostly side-effects rather than targeted intentions from where research is going (where it's funded). The vast majority of ML/AI work is focused on hijacking people's private data to steal their attention and psychologically manipulate them.
- UnFleshedOne 6y ago
  "Not working as good" is not the same as "actively working against". Unless of course a perfect Aryan visage serves as a master key to all face-locked phones.
  - bobyfyfy 6y ago
    The question wasn't "which ML use cases are potentially good", it was "which ML use cases are seen as predatory by users". So it doesn't matter that face detection has the possibility to be good, it's currently bad
    - UnFleshedOne 6y ago
      Bad, but not predatory. For example most speech recognition systems I tried often produce hilarious results with my accent, but I don't feel the tech is out to get me, it is just less than useless. On the other hand something like ad-tech feels more dangerous the better it works, to the point that I employ active countermeasures.
masswerk 6y ago
> Recommender engines Not so sure about these. Personally, I mostly feel deprived of options. (E.g., I guess, there are some videos uploaded to YT every day, and there must be more than some 3 months old news clips and those videos I've already seen, but it has actually become hard to learn about them. Therefore, in my personal YT universe, human creativity came mostly to a stop.)

tristor 6y ago

> * Recommender engines (e.g. music similar to the one I'm listening to) Is only ethical when opt-in, otherwise it violates user privacy to build preference profiles and requires additional private data to make accurate inferences. > Face unlocks for phones Heavily racially biased. Facial recognition in general is heavily racially biased. Other than that, I guess that's a good list. If ML stayed in those arenas it might be a net good, unfortunately those things on the list are mostly side-effects rather than targeted intentions from where research is going (where it's funded). The vast majority of ML/AI work is focused on hijacking people's private data to steal their attention and psychologically manipulate them.

UnFleshedOne 6y ago
"Not working as good" is not the same as "actively working against". Unless of course a perfect Aryan visage serves as a master key to all face-locked phones.
- bobyfyfy 6y ago
  The question wasn't "which ML use cases are potentially good", it was "which ML use cases are seen as predatory by users". So it doesn't matter that face detection has the possibility to be good, it's currently bad
  - UnFleshedOne 6y ago
    Bad, but not predatory. For example most speech recognition systems I tried often produce hilarious results with my accent, but I don't feel the tech is out to get me, it is just less than useless. On the other hand something like ad-tech feels more dangerous the better it works, to the point that I employ active countermeasures.

masswerk 6y ago

> Recommender engines Not so sure about these. Personally, I mostly feel deprived of options. (E.g., I guess, there are some videos uploaded to YT every day, and there must be more than some 3 months old news clips and those videos I've already seen, but it has actually become hard to learn about them. Therefore, in my personal YT universe, human creativity came mostly to a stop.)