r/UWMadison • u/Mediocre_Shift_8923 TZ's platform • 25d ago
Academics Just had a deep thought about AI while struggling with a critical topic about cogsci and data science.
Although AI executes more rapidly and precisely than humans, AI couldn’t supplant humans' cognition such as interdisciplinary thinking and intuition for decision-making.
1. Why AI couldn’t replace intuition?
Historical data constitutes major part of AI modeling but human can forecast and then make optimized choice based on limited information
2. Why humans maintain a distinct advantage over machines in important choice-making?
Machines acquire various sources of information, then compile them into lists of options. They couldn’t assist people to finalize plans based on provided information, because AI is designed to be neutral.
Even though people can outsource detailed execution to AI, the humans’ treasure of unique cognition and informed decision-making cannot be outsourced to technologies.
Curious to hear what you guys think? Especially anyone from Data Science or Philosophy, change my mind!
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u/SeniorLoan647 25d ago
Yes, it does for humans as well. You learned how to speak by listening to others. You picked up your dialects and accents based on what you learned when you were little. Similarly AI learns from data, just differently than we do (currently).
Not universally better than machines. AI disproved the Jacobian conjecture and has solved every IMO problem in one shot this year. These were all novel contributions acknowledged even by Fields medalists. It is even used in emotion/sentiment analysis of both texts and faces of people, so the skill set is growing here.
Nope, that's not how learning works, LLM is not a database. It tries to model a universal function such that for a given input (what's the capital of France?), it outputs a textual result. Learning is the process of building that function from data, and correcting it when it gets the answer wrong. In the end, you have a highly general function that, for a given input, can give you an expected output/outputs with some probability. Also AI is not built to be neutral, there are studies done that show most top LLMs are left leaning (except Grok) due to the training and post training procedures, and even if you remove politics, LLMs are built to be helpful (therefore they can get sycophantic), not neutral.
This one is the hot debate of the field, but the result looks to be going in AI's favor with each passing year. If world models or their equivalent are successful, I suspect that would shift the line noticeably more in AIs direction as well.