From quickly skimming through the article, it is solely about copyright rather than the environmental impact, employment, and the developers' ability to troubleshoot AI-generated code. As a man with an MSc in Data Science who does not work with genAI (not because I do not want to), I unironically love the topic. The 2D artists, whose livelihoods were affected by it, have significantly stronger feelings. Their logic is that whether or not you would have paid a person for the work, the models you've used likely were trained on their work. I would say that (I think) the labour for the sake of it, i.e. if it does not produce anything or gain skills (or at least some satisfaction or financial compensation), is soul-crushingly pointless and has no inherent value. There are several aspects which when combined might make one less comfortable. LLMs (Large Language Models) are trained to be extremely confident, yet supportive and go with the user's suggestions, because humans perceive confidence as knowledge (and there is some link between the eloquence and the perceived intelligence, which negatively affects primarily immigrants). LLMs are prediction models and do not possess any "ground truth", just a lot of data with different weights attached. They can work well for data summarisation or for some generic data, but less so for the niche subjects (and if you are unfamiliar with the field, you might not be able to spot errors). At the moment, the older models are provided for free to build reliance on them, as the skills unused deteriorate, so it is expected to lead to dependence (I can tell that I cannot easily multiply 3+ digit numbers without writing them down). You can see the similar pattern (en****tification) of building a user base, then extracting value from it in the other industries, such as video streaming. For software development in particular, I've been told that Claude Opus is a fantastic tool to use. The gotcha being that the developers must understand and be able to troubleshoot the code it generates, otherwise, the software will be impossible to support long-term. There are some other drawbacks and use cases and most are summarised in Abigail Thorn's video (1h): https://www.youtube.com/watch?v=AaU6tI2pb3M If you do need an LLM in your life, I would still suggest running one locally (can be done with a £700 Mac Mini M2).