One of LLMs main strengths over traditional text analysis tools is the ability to “understand” context.
They are bad at generating factual responses. They are amazing at analysing text.
Comment on AI Seeks Out Racist Language in Property Deeds for Termination
knightly@pawb.social 2 days agoThe use of LLMs instead of someone that can actually understand context.
GetOffMyLan@programming.dev 2 days ago
knightly@pawb.social 2 days ago
LLMs neither understand nor analyze text. They are statistical models of the text they were trained on. A map of language.
And, like any map, they should not be confused for the territory they represent.
If you admit that they have issues with facts, why would you assume that the randomly generated facts their “analysis” produces must be accurate?
GetOffMyLan@programming.dev 2 days ago
I mean they literally do analyze text. They’re great at it. Give it some text and it will analyze it really well. I do it with code at work all the time.
Because they are two completely different tasks. Asking them to recall information from their training is a very bad use. Asking them to analyze information passed into them is what they are great at.
Give it a sample of code and it will very accurately analyse and explain it. Ask it to generate code and the results are wildly varied in accuracy.
apotheotic@beehaw.org 2 days ago
The person you’re replying to is correct though. They do not understand, they do not analyse. They generate (roughly) the most statistically likely answer to your prompt, which may very well end up being text representing an accurate analysis. They might even be incredibly reliable at doing so. But this person is just pushing back against the idea of these models actually understanding or analysing. Its slightly pedantic, sure, but its important to distinguish in the world of machine intelligence.
t3rmit3@beehaw.org 2 days ago
I think you may have misunderstood the purpose of this tool.
It doesn’t read the deeds, make a decision, and submit them for termination all on its own. It reads them, identifies racial covenants based on patterns of language (which is exactly what LLMs are very good at), and then flags them for a human to review.
This tool is not replacing jobs, because the whole point is that these reviews were never going to get the budget and manpower to be done manually, and instead would have simply remained on the books.
I get being disdainful or even angry about LLMs in our unregulated-capitalism anti-worker hellhole because of the way that most companies are using them, but tools aren’t themselves good or bad, they’re just tools. And using a tool to identify racial covenants in legal documents that otherwise would go un-remediated, seems like a pretty good use to me.
knightly@pawb.social 2 days ago
So, what? They’re going to pay a human to OK the output and the whole lot of them never even gets seen?
Say 12 minutes per covenant, that’s 1 million work hours that humans could get paid for. Pay them $50 an hour and it’s $50 million. That’s nothing, less than 36 hours worth of the $12.5 Billion in weapons shipments we’ve sent to Israel in the last year. We could pay for projects like this with the rounding errors on the budget for blowing up foreign kids, and the people we pay to do it could afford to put their kids through college.
Instead, we get a project to train a robotic bigotry filter for real estate legalese and 50 more cruise missiles from the savings.
t3rmit3@beehaw.org 2 days ago
I think you are confused about the delineation between local and federal governments. It’s not all one giant pool of tax money.
knightly@pawb.social 2 days ago
I am not, I simply don’t believe the delineation is relevant since taxpayers fund both the state and federal budgets.
This is me being “reasonable” and working within the constraints of the system. If we aren’t going to have free universal college et al then we can at least trade some of the bloated military budget for a public works program.
Sounds to me like a 50% improvement over zero human eyes.
Why not? We could hire three teams to do it simultaneously in every state in the country and the cost would still be a tiny fraction of how much was wasted on the F-35 program.