I think that the problem arises because people equate things that are not the same. One person learning something is good. At scale, that becomes everyone lear

I think that the problem arises because people equate things that are not the same. One person learning something is good. At scale, that becomes everyone learning something. That's even better. Machine learning is not scaling up people learning. It's completely different even if it's called "learning". As the article argues, it's plagiarism at scale. In that sense, one person plagiarizing content is bad. Everyone plagiarizing at scale by using LLMs is even worse.