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> There's no difference between an art student looking through a museum or archives for ideas and an AI using the material for training. A few notable differen
by musicale 3y ago
> There's no difference between an art student looking through a museum or archives for ideas and an AI using the material for training.
A few notable differences:
1. Scale: a single art student can't view millions of works in a week.
2. Duplication: a single art student's brain can't be cloned or downloaded into another art student's brain.
3. Speed: a single art student cannot draw or paint thousands of images in a week.
4. Ownership: the software is likely owned and controlled by a large corporation, while the art student (hopefully) isn't.
- failbuffer 3y agoIf an art student was able to gain those abilities, would you then argue they couldn't legally create art?
- impomura 3y ago[flagged]
- deleted 3y ago[deleted]
- nl 3y agoThese are all true. But they apply equally to a search engine index and that has already been found not to violate copyright and to be very useful to society.
- musicale 3y ago> These are all true That was the point. Whether or not there is copyright infringement going on (or whether copyright law is an appropriate regulatory framework for ML models), I frequently see claims like "ML training is no different from what humans do" repeated, in spite of its incorrectness.
- bastawhiz 3y agoNotably none of those things, if they did apply to the art student, are copyright violations. The speed, scale, versatility, and ownership of a machine learning model has no bearing on its ability to violate copyright.
- Riverheart 3y agoGood reasons not to assign copyright to their output, at least not without some caveats.
- bastawhiz 3y agoI don't have strong feelings about that either way, but that's not what this post is about.
- musicale 3y agoThe interesting thing to me is determining when something that is acceptable for humans to do at human scale is also acceptable for machines to do at industrial scale. There are many examples. One is face recognition - clearly it is acceptable for individual humans to do this at small scale, but systematic identification of everyone on a street or in a stadium has different implications for society. (In this case it almost doesn't matter whether the surveillance is performed by humans or machines - it's the scale and systematic nature that changes the equation.)
- swfsql 3y agoThis just means students better grow bigger brains!