First, although GPT-4’s UBE score nears the 90th percentile when examining approximate conversions from February administrations of the Illinois Bar Exam, these estimates are heavily skewed towards repeat test-takers who failed the July administration and score significantly lower than the general test-taking population.
What I find delightful about this is that I already wasn't impressed! Because, as the paper goes on to say
Moreover, although the UBE is a closed-book exam for humans, GPT-4’s huge training corpus largely distilled in its parameters means that it can effectively take the UBE “open-book”
And here I was thinking it not getting a perfect score on multiple-choice questions was already damning. But apparently it doesn't even get a particularly good score!
[...W]hen examining only those who passed the exam (i.e. licensed or license-pending attorneys), GPT-4’s performance is estimated to drop to 48th percentile overall, and 15th percentile on essays.
officially Not The Worst™, so clearly AI is going to take over law and governments any day now
also. what the hell is going on in that other reply thread. just a parade of people incorrecting each other going "LLM's don't work like [bad analogy], they work like [even worse analogy]". did we hit too many buzzwords?
Not the worst? 48th percentile is basically "average lawyer". I don't need a Supreme Court lawyer to argue my parking ticket. And if you train the LLM with specific case law and use RAG can get much better.
In a worst case scenario if my local lawyer can use AI to generate a letter and just quickly go through it to make sure it didn't hallucinate, they can process more clients, offer faster service and cheaper prices. Maybe not a revolution but still a win.
good thing all of law is just answering multiple-choice tests
I don't need a Supreme Court lawyer to argue my parking ticket.
because judges looooove reading AI garbage and will definitely be willing to work with someone who is just repeatedly stuffing legal-sounding keywords into google docs and mashing "generate"
And if you train the LLM with specific case law and use RAG can get much better.
"guys our keyword-stuffing techniques aren't working, we need a system to stuff EVEN MORE KEYWORDS into the keyword reassembler"
In a worst case scenario if my local lawyer can use AI to generate a letter
oh i would love to read those court documents
and just quickly go through it to make sure it didn't hallucinate
wow, negative time saved! okay so your lawyer has to read and parse several paragraphs of statistical word salad, scrap 80+% of it because it's legalese-flavored gobbledygook, and then try to write around and reformat the remaining 20% into something that's syntactically and legally coherent -- you know, the thing their profession is literally on the line for. good idea
what promptfondlers continuously seem to fail to understand is that verification is the hard step. literally anyone on the planet can write a legal letter if they don't care about its quality or the ramifications of sending it to a judge in their criminal defense trial. part of being a lawyer is being able to tell actual legal arguments from bullshit, and when you hire an attorney, that is the skill you are paying for. not how many paragraphs of bullshit they can spit out per minute
they can process more clients, offer faster service and cheaper prices. Maybe not a revolution but still a win.
"but the line is going up!! see?! sure we're constantly losing cases and/or getting them thrown out because we're spamming documents full of nonsense at the court clerk, but we're doing it so quickly!!"
Why is that a criticism? This is how it works for humans too: we study, we learn the stuff, and then try to recall it during tests. We've been trained on the data too, for neither a human nor an ai would be able to do well on the test without learning it first.
This is part of what makes ai so "scary" that it can basically know so much.
Because a machine that "forgets" stuff it reads seems rather useless... considering it was a multiple choice style exam and, as a machine, Chat GPT had the book entirely memorized, it should have scored perfect almost all the time.
You ever meet an ai researcher with a background in biology? I’ve discussed this stuff with one. She disagrees with Turing about machines thinking including when ai is in the picture. They process information very differently from how biology does
so to summarize, your only contributions to this thread are to go “well uh you just don’t know how LLMs work” while providing absolutely no detail of your own, and reporting our regulars for “Civility” when they rightly called you out for being a fucking idiot who’s way out of their depth
Well... I do agree with you but human brains are basically big prediction engines that use lookup tables, experience, to navigate around life. Obviously a super simplification, and LLMs are nowhere near humans, but it is quite a step in the direction.
I guess it comes down to a philosophical question as to what "know" actually means.
But from my perspective is that it certainly knows some things. It knows how to determine what I'm asking, and it clearly knows how to formulate a response by stitching together information. Is it perfect? No. But neither are humans, we mistakenly believe we know things all the time, and miscommunications are quite common.
But this is why I asked the follow up question...what's the effective difference? Don't get me wrong, they clearly have a lot of flaws right now. But my 8 year old had a lot of flaws too, and I assume both will get better with age.