I’ve been very fed up with AI for about past 6 months, completely started to boycott it, discuss it with people of all kinds of different views, and I found joy and pride once again in my own work.
But the world issues coming from AI, and even more so from the billionaires and empires behind it seem to further pile up to insane heights. I’ve been trying to learn more and more about it, and after my bachelor and masters I am considering pursuing phd and research surrounding AI, especially from the critical perspective, which seems to be deeply neglected in the research pov.
This is still a few years in the future, and lot could change, but I am curious what do people here think about pursuing such a thing, and if in current academic world it is even something that would be possible doing, given lot of the grants and funding of AI research comes from these companies that just want to gain even more power through it.
As I said, I am already trying to know as much as possible about it, but I would like to look more deeply into its impact on society, impact on students etc.
Do you think this would be a worthwile endevaour? And if not, where do you think I should be heading to make change about this while not completely starving to death?
I think if you open up a study, you should and probably need to be specific with the terms. Since llms are just large machine learning models. Just not trained for a single specific use case. You can also achieve very impressive results with small models, you don’t need chatgpt 5 for document classification. You can also fine-tune these models for specific tasks and/or “lobotomize” them. But f.e. go with a small qwen model with just 36B parameters or less and you will get very good results. And sure there are the good old OCR methods but you’ll need a significant pipeline behind a classic ocr machine. And it would probably still fail to decipher/classify a machine written document with hand written annotations. When you use a decent LLM, it will in most cases be able to differentiate between handwriting & machine letters, it will be able to output both in different variables and it might even be able to put the annotations in context to the original document. And this is an enormous task to program by hand.
And when we talk about speed and sustainability, not every document would be thrown at the expensive model first. But you would build a layered approach, so that 95% of the easy documents would be handled by a cheap and fast solution, but when that has a low confidence, then you would hand the document over to the bigger slower model.
Then add graphs or tables to the document and you’ll be nearly completely lost with a classic approach.
I’ve been working in this field for a couple years, so I speak from personal experience.
But still all those models still have an issue with context sizes and you and your business pipeline will fail if you don’t know the boundaries of what’s possible today. For the most high profile cases there should always be a human in the loop. Do companies do that? Most likely not, but they can get in big trouble if they make a critical mistake, at least in Europe, can’t speak for the wild West/US.
Note: You can self host qwen3.6 with 32gb or better 64gb and play it. It is shockingly good.
Data gathering and theft of IP is a completely different topic. But “luckily” many people now upload their data for free, directly to one of the big hosting companies. But privacy is also a different topic.
So again, be very specific if you choose your topic.
Of course yeah, if I would be writing actual research I would be more concious of the terms used. I see you have a lot of experience and have been using LLMs a lot and searching for ways to use them conciously, and that’s kind of part of the reason I would like to study them (and Machine Learning in general) more deeply. You seem to have the practical experience, but I would also like to personally look into it with the academic view, and see how these arguments really stand and how to improve the actual uses, while pushing against the bogus uses and claims that many people and mostly companies keep telling us. There’s still many years until then, maybe I’ll choose a different path to push against companies and the bullshit we are dealing with today… But I think this field might be something I am genuinely interested, and if I may actually do some worthwhile change during it, it would be a nice bonus…
I’d say most people who successfully run llms and do use it consciously are actual “AI-engineers” with a proper computer science background.
The people i’ve met who shout the loudest about their ai use are usually nothing burgers or management positions who didn’t come from an IT background and just see the golden goose “Ai” and want a piece of it.
If you want to get in touch with people having experience go and look for meetups :)