I see this type of reduction again and again to advocate for one position or another relating to ML. Human consciousness and thought processes aren’t “just” anything (math, electrical impulses, etc.) — the fact is, we don’t know what the brain really does and how it’s connected to our conscious experience, or even what that is!
Deep learning is very powerful and impressive in its applications to date. However, it’s so saturated with hype (and humans are so prone to anthropomorphizing things) that it’s often viewed as something much more profound than it actually is. Neural networks, despite their name, don’t model the brain. And they lack a whole array of “intelligence” features that humans possess and use constantly.
All of this is to say that there are very significant differences between computer algorithms and human cognition, and I tend to think the legal system will be unpersuaded by arguments that ignore those differences.
Also, this is to say nothing of the public policy interests that shape the law. Regardless of what’s “under the hood,” the law can simply treat human and machine output differently. I’m not a copyright lawyer, of course, so I can’t speak to the norms or technicalities of copyright law itself.
> Human consciousness and thought processes aren’t “just” anything (math, electrical impulses, etc.) — the fact is, we don’t know what the brain really does and how it’s connected to our conscious experience, or even what that is!
There are a lot of things we don’t know, but it is not magic. There is no discussion that artificial neurones don’t have much in common with the real ones, which are very non-linear and much more connected. But in the end it’s all electrochemistry.
> Neural networks, despite their name, don’t model the brain.
But that’s not directly related to my point. My point that even in the case of a ML model, you cannot get an exact reproduction any more than you can get from a human’s memory. In one case it’s scrambled somewhere in someone’s brain, in the other on a hard drive but the difference is not really relevant. Subjecting an AI’s production to the copyrights of all the things it’s been exposed to is very similar to subjecting a painter’s production to the copyrights of all the painting they have seen.
Deep learning is very powerful and impressive in its applications to date. However, it’s so saturated with hype (and humans are so prone to anthropomorphizing things) that it’s often viewed as something much more profound than it actually is. Neural networks, despite their name, don’t model the brain. And they lack a whole array of “intelligence” features that humans possess and use constantly.
All of this is to say that there are very significant differences between computer algorithms and human cognition, and I tend to think the legal system will be unpersuaded by arguments that ignore those differences.
Also, this is to say nothing of the public policy interests that shape the law. Regardless of what’s “under the hood,” the law can simply treat human and machine output differently. I’m not a copyright lawyer, of course, so I can’t speak to the norms or technicalities of copyright law itself.