C) I’m a Data Science major who’s gonna be looking for full-time work in the tech sector starting next semester. Given that the work I’m aiming to gt into will use a lot of machine learning and repeated tests, using AI like LLMs is going to be very useful (and likely essential) for handling the bottleneck of taking up a lot of time to draft boilerplate code and setting up tests for models. Also, a lot of companies are pushing their engineers to use AI for their work, likely to keep up an output rate that the bosses would want you to have. Their philosophy being it’s better to prototype multiple times and amend it rather than writing the code from scratch and then looking up documentation for syntax things. I think if you want to work in the tech sector in a decently sized company you wouldn’t really have a choice to not use AI. At some point, your managers would get on your case for not having an output as fast as your coworkers (the quality of their code would be irrelevant). For myself personally, I’ve found LLMs very useful in my coding (for personal projects and for a research project I’m currently working on) for the boilerplate code, but knowing the logic for what functions and such to use is still very important for human engineers. An example of this already impacting people is for ex. Meta, who is starting to have AI-Assisted coding interviews. companies are definitely pushing people, and other companies, to use AI in their work. The main issue is definitely environmental on a corporate scale. Companies should not be allowed to cheap out on their payment for evnironmental resource use that Data Centers takes advantage of, especially in small towns.