Stanford University researchers unveiled an AI model they say can analyze decades of property records in just a few days at little expense to weed out racist language, and they will offer the tool for free across the state and around the country.
Santa Clara County alone has 24 million property records, but the study team focused mostly on 5.2 million records from the period 1902 to 1980. The artificial intelligence model completed its review of those records in six days for $258, according to the Stanford study. A manual review would have taken five years at a cost of more than $1.4 million, the study estimated.
This is an awesome use of an LLM. Talk about the cost savings of automation, especially when the alternative was the reviews just not getting done.
Specialized LLMs trained for specific tasks can be immensely beneficial! I’m glad to see some of that happening instead of “Company XYZ is now needlessly adding AI to it’s products because buzzwords!”
LLMs are bad for the uses they’ve been recently pushed for, yes. But this is legitimately a very good use of them. This is natural language processing, within a narrow scope with a specific intention. This is exactly what it can be good at. Even if does have a high false negative rate, that’s still thousands and thousands of true positive cases that were addressed quickly and cheaply, and that a human auditor no longer needs to touch.
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.
I’m not assuming anything you can literally go and use one right now and see.
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.
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.
I think you are confused about the delineation between local and federal governments. It’s not all one giant pool of tax money. None of Santa Clara County’s budget goes to missiles.
Also, this feels like you are too capitalism-pilled, and rather than just spending the $240 to do this work, and using the remaining $49,999,760 to just fund free college or UBI programs, you’re like, “how about we pay these people to do the most mind-numbingly, soul-crushingly boring work there is, reading old legal documents?”
You know what would actually happen if you did that? People would seriously read through them for 1 day, and then they’d be like, “clear”, “clear”, “clear” without looking at half of them. It’s not like you’re gonna find and fund another group to review the first group’s work, after all. So you’d still be where we are now, but you also wasted x* peoples’ time that they could have been enjoying doing literally anything else.
This is an awesome use of an LLM. Talk about the cost savings of automation, especially when the alternative was the reviews just not getting done.
Specialized LLMs trained for specific tasks can be immensely beneficial! I’m glad to see some of that happening instead of “Company XYZ is now needlessly adding AI to it’s products because buzzwords!”
Did you see something that said it was an LLM?
Edit: Indeed it’s an LLM. They published the model here: https://huggingface.co/reglab-rrc/mistral-rrc
Given the error rate of LLMs, it seems more like they wasted $258 and a week that could have been spent on a human review.
LLMs are bad for the uses they’ve been recently pushed for, yes. But this is legitimately a very good use of them. This is natural language processing, within a narrow scope with a specific intention. This is exactly what it can be good at. Even if does have a high false negative rate, that’s still thousands and thousands of true positive cases that were addressed quickly and cheaply, and that a human auditor no longer needs to touch.
What do you believe would make this particular use prone to errors?
The use of LLMs instead of someone that can actually understand context.
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.
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?
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.
I’m not assuming anything you can literally go and use one right now and see.
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.
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.
I think you are confused about the delineation between local and federal governments. It’s not all one giant pool of tax money. None of Santa Clara County’s budget goes to missiles.
Also, this feels like you are too capitalism-pilled, and rather than just spending the $240 to do this work, and using the remaining $49,999,760 to just fund free college or UBI programs, you’re like, “how about we pay these people to do the most mind-numbingly, soul-crushingly boring work there is, reading old legal documents?”
You know what would actually happen if you did that? People would seriously read through them for 1 day, and then they’d be like, “clear”, “clear”, “clear” without looking at half of them. It’s not like you’re gonna find and fund another group to review the first group’s work, after all. So you’d still be where we are now, but you also wasted x* peoples’ time that they could have been enjoying doing literally anything else.