This is one of the domains I'm very very excited about for LLMs to help me with. In 5-10 years (even though this research paper makes me feel its already here), I would feel very confident chatting for a few hours with a "lawyer" LLM that has access to all my relevant taxes/medical/insurance/marriage documents and would be able to give me specialized advice and information without billing me $500 an hour.
A wave of (better) legally informed common-person is coming, and I couldn't be more excited!
I wouldn't blindly trust what the LLM says, but I take it that it would be mostly right, and that would give me at the very least explorable vocabulary that I can expand on my own, or keep grilling it about.
I've already used some LLMs to ask questions about licenses and legal consequences for software related matters, and it gave me a base, without having to involve a very expensive professional into it for what are mostly questions for hobby things I'm doing.
If there was a significant amount of money involved in the decision, though, I will of course use the services of a professional. These are the kinds of topics you can't be "mostly right".
I don't understand how everyone keeps making this mistake over and over.
They explicitly just said "in 5-10 years".
So many people continually use arguments that revolve around 'I used it once and it wasn't the best and/or me things up', and imply that this will always be the case.
There are many solutions already for knowledge editing, there are many solutions for improving performance, and there will very likely continue to be many improvements across the board for this.
It took ~5 years from when people in the NLP literature noticed BERT and knew the powerful applications that were coming, until the public at large was aware of the developments via ChatGPT.
It may take another 5 before the public sees the developments happening now in the literature hit something in a companies web UI.
> It took ~5 years from when people in the NLP literature noticed BERT and knew the powerful applications that were coming, until the public at large was aware of the developments via ChatGPT. It may take another 5 before the public sees the developments happening now in the literature hit something in a companies web UI.
It also may take 10, 20, 50, or 100 years. Or it may never actually happen. Or it may happen next month.
The issue with predicting technological advances is that no one knows how long it'll take to solve a problem until it's actually solved. The tech world is full of seemingly promising technologies that never actually materialized.
Which isn't to say that generative AI won't improve. It probably will. But until those improvements actually arrive, we don't know what those improvements will be, or how long it'll take. Which ultimately means that we can only judge generative AI based on what's actually available. Anything else is just guesswork.
I'm concerned that until they do improve, we're in a weird place. For example, if you were 16, would you go an invest a bunch of time and money to study law with the prospect of this hanging of your future? Same for radiology, would you go study that now Geoffrey Hinton has proclaimed the death of radiologists in 3 years or whatever? Photography and filmography ?
My concern is we're going to get to a place where we think the machines can just take over all important professions, but they're not quite there yet, however people don't bother learning those professions because they're a career dead end and then we just end up with a skill shortage and mediocre services, when something goes wrong, you just have to trust "the machine" was correct.
How do we avoid this? Almost like we need government funded "career insurance" or something like this.
I'm not so sure that truth and trustability is something we can just hand-wave away as something they'll sort out in just a few more years. I don't think a complex concept like whether or not something is actually true can be just tacked onto models whose core function is to generate what they think the next word of a body of text is most likely to be.
on the other hand the rate of change isn't constant and there isn't a guarantee that the incredible progress in the past ~2 years in the LLM/diffusion/"AI" space will continue. As an example, take computer gaming graphics; compare the evolution between Wolfenstein 3D (1992) and Quake 3 Arena (1999), which is an absolute quantum leap. Now compare Resident Evil 7 (2017) and Alan Wake 2 (2023) and it's an improvement but nowhere near the same scale.
We've already seen a fair bit of stagnation in the past year as ChatGPT gets progressively worse as the company is more focusing on neutering results to limit its exposure to legal liability.
Yes again, it's very strange to see a simple focus on one particular instance from one particular company to represent the entire idea of technology in general.
If windows 11 is far worse in many metrics than windows XP or Linux, does that mean that technology is useless?
It's one instance of something with a very particular vision being imposed. Windows 11 being slow due to reporting several GB of user data in the first few minutes of interaction with the system does not mean that all new OS are slow. Similarly, some older tech in a web UI (ChatGPT) for genAI producing non-physical data does not mean that all multimodal models will produce data unsupported by physics. Many works have already shown a good portion of the problems in GPTs can be fixed with different methods stemming from rome, rl-sr, sheavNNs, etc.
My point isn't even that certain capabilities may get better in the future, but rather that they already are better now, just not integrated into certain models.
That website doesn't load for me but anyone who uses ChatGPT semi regularly can see that it's getting steadily worse if you ever ask for anything that begins to border risque. It has even refused to provide me with things like bolt torque specs because of risk.
It could be a bias, that's why we do blinded comparisons for a more accurate rating. If we have to consider my opinion, since I use it often, then no, it hasn't gotten worse over time.
Well I can't load that website so I can't assess their methodology. But I am telling you it is objectively worse for me now. Many others report the same.
Edit - the website finally loaded for me and while their methodology is listed, the actual prompts they use are not. The only example prompt is "correct grammar: I are happy". Which doesn't do anything at all to assess what we're talking about, which is ChatGPT's inability to deal with subjects which are "risky" (where "risky" is defined as "Americans think it's icky to talk about").
Worse is really subjective. More limited functionality with a specific set of topics? Sure. More difficult to trick to get around said topic bans? Sure.
Worse overall? You can use chatgpt 4 and 3.5 side by side and see an obvious difference.
Your specific example seems fairly reasonable. Is there liability in saying x bolt can handle y torque if that ended up not being true? I don't know. What is that bolt causes an accident and someone dies? I'm sure a lawyer could argue that case if ChatGPT gave a bad answer.
No. Malpractice insurance would be at the professional level. There could be lawyers using a legal chatGTP, but the professional liabilities would still be with the licensed professional.
More legal malpractice? No, because they aren't attorneys and you cannot rely upon them for legal advice such that they'd be liable to you for providing subpar legal advice.
Why? Because there's no word for "insurance of AI advise accuracy"? The whole point of progress is that we create something that is not a thing at the moment.
No, because, like I said, GPTs are not legally allowed to represent individuals, so they cannot obtain malpractice insurance. You can make up an entirely ancillary kind of insurance. It does not change the fact that GPTs are not legally allowed to represent clients, so they cannot be liable to clients for legal advice. Seeing as how you think GPTs are so useful here... why are you asking me these questions when a GPT should be perfectly capable of providing you with the policy considerations that underline attorney licensing procedures.
I like the term "explorable vocabulary." I can see using LLMs to get an idea of what the relevant issues are before I approach a professional, without assuming that any particular claim in the model's responses is correct.
This is an area for further development and thought...
If a LLM can pass the bar, and has a corpus of legal work instantly accessible, what prevents the deployment of the LLM (or other AI structure) to provide legitimate legal services?
If the AI is providing legal services, how do we assign responsibility for the work (to the AI, or to its owner)? How to insure the work for Errors and Omissions?
More practically, if willing to take on responsibility for yourself, is the use of AI going to save you money?
A human that screws up either too often or too spectacularly can be disbarred, even if they passed the bar. They can also be sued. If a GPT screws up, it could in theory be disbarred. But you can't sue it for damages, and you can't tell whether the same model under a different name is the next legal GPT you consult.
> If a LLM can pass the bar, and has a corpus of legal work instantly accessible, what prevents the deployment of the LLM (or other AI structure) to provide legitimate legal services?
The law, which you can bet will be used with full force to prevent such systems from upsetting the (obscenely profitable) status quo.
Re your first point: it's not conscious. It has no understanding. It's perfectly possible the model could successfully answer an exam question but fail to reach the same or similar conclusion when it has to reason it's own way there based on information provided.
Great point, LLM will not be great at ground breaking law.... But most lawyers aren't. That's to say, most law isn't cutting edge. The law is mostly a day-to-day administrative matter
Careful, there are plenty of True Believers on this website who really think that these "guess the next word" machines really do have consciousness and understanding.
The obvious intermediate step is that you add an actual expert into the workflow, in terms of using LLMs for this purpose.
Basically, add a "validate" step. So, you'd first chat with the LLM, create conclusions, then vet those conclusions with an expert specially trained to be skeptical of LLM generated content.
I would be shocked if there aren't law agencies that aren't already doing something exactly like this.
What if they were liable? Say the company that offers the LLM lawyer is liable. Would that make this feasible? In terms of being convincingly wrong, it's not like lawyers never make mistakes...
You'd require them to carry liability insurance (this is usually true for meat lawyers as well), which basically punts the problem up to "how good do they have to be to convince an insurer to offer them an appropriate amount of insurance at a price that leaves the service economically viable?"
Given orders of magnitude better cost efficiency, they will have plenty of funds to lure in any insurance firm in existence. And then replace insurance firms too.
"In terms of being convincingly wrong, it's not like lawyers never make mistakes..."
They have malpractice insurance, they can potentially defend their position if later sued, and most importantly they have the benefit of appeal to authority image/perception.
All right, what if legal GPTs had to carry malpractice insurance? Either they give good advice, or the insurance rates will drive them out of business.
I guess you'd have to have some way of knowing that the "malpractice insurance ID" that the GPT gave you at the start of the session was in fact valid, and with an insurance company that had the resources to actually cover if needed...
Weirdly HN is full of anti AI people who just refuses to discuss the point that is being discussed and goes into all the same argument of wrong answer that they got some time. And then they present anecdotal evidence as truth, while there is no clear evidence if AI lawyer has more or less chance to be wrong than human. Surely AI could remember more and has been shown to clear bar examination.
"while there is no clear evidence if AI lawyer has more or less chance to be wrong than human."
In the tests they are shown to be pretty close. The point I made wasn't about more mistakes, but about other factors influencing liability and how it would be worse for AI than humans at this point.
This is the key point. Even if assume the AI won't get better, the liability and insurance premiums will likely become similar in very near future. There is a clear business opportunity that's there in insuring AI lawyer.
Our core business is legal document generation (rule based logic, no AI). Since we already have the users' legal documents available to us as a result of our core business, we are perfectly positioned to build supplementary AI chat features related to legal documents.
We recently deployed a product recommendation AI to prod (partially rule based, but personalized recommendation texts generated by GPT-4). We are currently building AI chat features to help users understand different legal documents and our services. We're intending to replace the first level of customer support with this AI chat (and before you get upset, know that the first level of customer support is currently a very bad rule-based AI).
Main website in Finnish: https://aatos.app (also some services for SE and DK, plus we recently opened UK with just a e-sign service)
So, let’s say that the chat will work as well as the real lawyer some day.
If the current pricing would be $500 an hour for a real lawyer, and at some point your costs are just keeping services up and running, how big cut will you take? Because it is enough if you are only a little cheaper than the real lawyer to win customers.
There is an upcoming monopoly problem, if the users get the best information from the service after they submit all their documents. And soon the normal lawyer might be competitive enough. I fear that the future is in the parent commenter’s open platfrom with open models and the businesses should extract money from some other use cases, while for a while, you get money momentarily based on the typical ”I am first, I have the user base” situation. It is interesting to see what will happen to lawyers.
> If the current pricing would be $500 an hour for a real lawyer, and at some point your costs are just keeping services up and running, how big cut will you take?
Zero. We're providing the AI chat for free (or free for customers who purchase something from us, or some mix of those 2 choices). Our core business is generating documents for people, and the AI chat is supplementary to the core business.
It sounds like you're approaching the topic with the mindset that lawyers might be entirely replaced by automation. That's not what we're trying to do. We can roughly divide legal work into 3 categories:
1. Difficult legal work which requires a human lawyer to spend time on a case by case basis (at least for now).
2. Cookie cutter legal work that is often done by a human in practice, but can be automated by products like ours.
3. Low value legal issues that people have and would like to resolve, but are not worth paying a lawyer for.
We're trying to supply markets 2 and 3. We're not trying to supply market 1.
For example, you might want a lawyer to explain to you what is the difference between a joint will and an individual will in a particular circumstance. But it might not be worth it to pay a lawyer to talk it through. This is exactly the type of scenario where an AI chat can resolve your legal question which might otherwise go unanswered.
> It sounds like you're approaching the topic with the mindset that lawyers might be entirely replaced by automation.
That is the cynical future, however, and based on the evolution speed of the last year, it is not too far away. We humans are just interfaces for information and logic.
If the chatbot has the same capabilities (both information and logic, and natural language), then they will provide full automation.
The natural language aspect of AI is the revolutionary point, less about the actual information they provide. Quoting Bill Gates here, like the GUI was revolutionary. When everyone can interact and use something, it will remove all the experts that you needed before as middle man.
Here's an example of what our product recommendations look like:
Given your ownership in a company and real estate, a lasting power of attorney is a prudent step. This allows you to appoint PARTNER_NAME or another trusted individual to manage your business and property affairs in the event of incapacitation. Additionally, it can also provide tax benefits by allowing tax-free gifts to your children, helping to avoid unnecessary inheritance taxes and secure the financial future of your large family.
> Since we already have the users' legal documents available to us as a result of our core business, we are perfectly positioned to build supplementary AI chat features related to legal documents.
If you look at the example I posted of our product recommendations, you will see that the GPT-4 generated text contains "PARTNER_NAME" instead of actual partner name. That's because we've created anonymized dataset from users in such a way that it's literally impossible for OpenAI to deanonymize users. Of course the same can not be done if we want to provide a service where users can, for example, chat with their legal documents. In that case we will have to send some private details to OpenAI. Not sure how that will pan out (what details we decide to send and what we decide not to send).
In any case, all startups today are created on top of a mountain of cloud services. Any one of those services can leak private user data as a result of outsider hack or insider attack or accident. OpenAI is just one more cloud service on top of the mountain.
Or a LLM that helps you spend less. Imagine a LLM that goes over all your spending, knows all the current laws, benefits, organizations, promotional campaigns, and suggests (or even executes) things like changing electricity provider, insurance provider, buying stuff in bulk from a different shop that you get for 4x the price at your local store, etc.
Yup. Because the doctor doesn't have time and doesn't give a fuck.
LLMs don't have to compete against the cutting edge of human professional knowledge. They only have to compete against the disinterested, arrogant, greedy, and overworked professionals that are actually available to people in practice. No wonder they're winning.
This is a really interesting use case for me. I've been envisioning a specially trained LLM that can give useful advice or insights that your average PCP might gloss over or not have the time to investigate.
Did you do anything special to achieve this? What were the results like?
I think a lot of startups are working on exactly what you are describing, and honestly, I wouldn't hold my breath. Everyone is still bound by token limits and the two best approaches for getting around them are RAG and Knowledge-Graphs, both of which could get you close to what you describe but not close enough to be useful (IMO).
This does not make sense to me. ChatGPT is completely nerfed to the point where it's either been conditioned or trained to provide absolutely zero concrete responses to anything. All it does is provide the most baseline, generic possible response followed by some throwaway recommendation to seek the advice of an actual expert.
The way to get around this is to have it "quote" or at least try to quote from input documents. Which is why RAG became so popular. Sure, it won't right you a contract, but it will read one back to you if you've provided one in your prompt.
In my experience, this does not get you close to what the top-level comment is describing. But it gets around the "nerfing" you describe
It's very easy to get ChatGPT to provide legal advice based on information fed in the prompt. OpenAI is not censoring legal advice anywhere near as hard as they are censoring politics or naughty talk.
That's because its just advice, not legal advice. Legal advice is something you get from an attorney that represents you. It creates a liability relationship between you and the attorney for the legal advice they did provide.
Sure, we can call it "advice" instead of "legal advice" or we can even call it other names, like "potato", if that's what you want. My point is that potato not censored.
A wave of (better) legally informed common-person is coming, and I couldn't be more excited!