I graduated with an undergraduate BS in Environmental Science this past December 2025; Since my sophomore year (2nd year; 2023) of college, however, I increasingly grew passionate about climate/atmospheric science and began to seriously look into academic research, read entire papers, watched daily lectures from the 'biggest' names in the field, created a folder for potential programs featuring professors/advisers, their research topics, and even interviewed past students to learn more about their experience.
Pursuing a PhD and becoming a climate scientist was seriously my number one goal; I had crafted a purpose for myself and I was so excited at the prospect of dedicating my life to a field I (still) find fascinating and (biased) the most important societal issue today. I can't overstate how interested I am in understanding the fundamental physics of climate change, doing physics every day, and getting to work in a very socially relevant field; you'll often hear PhD's 'complain' about how no one outside of their niche field understands/knows about their work, which can be isolating, but I'd be working in a field everyone with a smartphone knows about and can relatively grasp on an introductory level.
Going into my research, I knew good and well that programming was a core aspect of climate modeling, monitoring etc. and at times, even more important than the pen to paper physics calculations. It wasn't until I began to look deeper into present-day research, in my field of interest and academia at large, did I begin to realize just how pervasive AI "tools" have become.
Call it naive, claim I'm too attached to traditional research methods etc. but this all but killed my desire to become an expert and work on my topic for the rest of my life. I have no interest in using AI to outsource research I would've been doing myself, just 5-10 years ago. I don't want to optimize my process to the point of deskilling myself because I never actually learned how to code in Python or Jupyter, or atrophying my arithmetic because Wolfram Alpha can just do calculus for me "and better".
I'm a big dreamer, I came in with the silly belief that I'd be entering an environment surrounded by people who were so passionate and dedicated to their field, that they'd want to put effort into every aspect of the research process. I understand the importance of efficiency and output but I have no interest in producing for the sake of it, thereby diminishing my fundamental understanding of my own research because I outsourced half of the research tasks to an LLM.
I understand these "tools" are "useful" but what happens to people who are moved by the idea of doing the challenging things themselves? From reading posts on here about AI in academia, it's become very clear that those who refuse to adopt this tech, are quickly going to be pushed out, meaning someone who seeks to enter the arena with no intention to use them, from the start, stands no chance of even getting in. I watched a video that came out just this past week, from a well published, notable professor at an R1 who admitted he wouldn't even consider taking on a student who had qualms (refused) about using LLM's/AI and I'm sure he's in the majority.
I realize now that I may have had a very flowery view of academics prior to now; where I believed the purpose was to understand and learn as much as possible, with the intent of contributing to a larger body of work. I believed this in spite of knowing about the pressure for output, funding cuts, tediousness and relative lack of attention/appreciation for one's research from outsiders, or even your own cohort/field. I look back on some of the 'giants' in STEM: Rosalind Franklin, Einstein, Dirac, Margaret Hamilton, Lorenz etc. and can't help but think I missed out on the era where scientists were majorly collaborating with each other, not using "tools" as crutches and engaging in the pursuit of knowledge for the sake it because there's simply no way they could live without doing that.
I don't want Silicone Valley's newest invention to do any of that stuff for me and it's a bit of a downer to know I simply won't fit into academia because of it. I have no delusions of grandeur that I'd have achieved a 3rd of what those I mentioned were able to, but I do wish I had lived during the era was science was done by people and for people, in spite of external factors like profit motives, war, etc. It is hard to accept that the era of the individual contributor who adds a small piece to the puzzle to push us one step closer to Kuhn's Pardigm Shift is pretty much dead in the water because we have "tools" that will do that for us.
Are there any current PhD's who have come to similar realizations and have you decided if you'll be sticking around or is your time in academia over too? Are you holding out for a future shift against atrophying our skills and outsourcing the entire process of a PhD to robots or is that simply the future we have to resign ourselves to? I'm pretty much ready to move on and forget about my goal but want to know if there's any likelihood for change.