61–70 of 160 posts
Don't be too worried about LLM arms races. Law is not as complicated as it seems on TV. Having access to a better LLM isn't going to somehow give you access to the correct incantation necessary to dismiss a case. The vast majority, like 99.99% of cases, turn on completely understood legal issues. Everyone knows everything.
I saw a RAG demo from a startup that allows you to upload patient's medical docs, then the doctor can ask it questions like: > what's the patient's bp? even questions about drugs, histories, interactions, etc. The AI keeps in mind the patient's age and condition in its responses, when recommending things, etc. It reminded me of a time I was at the ER for a rib injury and could see my doctor Wikipedia'ing stuff - coul…
> It reminded me of a time I was at the ER for a rib injury and could see my doctor Wikipedia'ing stuff To be honest, I'm much more comfortable with a doctor looking things up on wikipedia than using LLMs. Same with lawyers, although the stakes are lower with lawyers. If I knew my doctor was relying on LLMs for anything beyond the trivial (RAGS or not), I'd lose a lot of trust in that doctor.
Doctors and lawyer appear to be using LLMs in fundamentally different ways. Doctors appear to use them as consultants. The LLM spits out an opinion and the Doctor decides whether to go with it or not. Doctors are still writing the drug prescriptions. Lawyers seem to be submitting LLM-generated text to courts without even editing it, which is like the Doctor handing the prescription pad to the robot.
I saw a RAG demo from a startup that allows you to upload patient's medical docs, then the doctor can ask it questions like: > what's the patient's bp? even questions about drugs, histories, interactions, etc. The AI keeps in mind the patient's age and condition in its responses, when recommending things, etc. It reminded me of a time I was at the ER for a rib injury and could see my doctor Wikipedia'ing stuff - coul…
> It reminded me of a time I was at the ER for a rib injury and could see my doctor Wikipedia'ing stuff To be honest, I'm much more comfortable with a doctor looking things up on wikipedia than using LLMs. Same with lawyers, although the stakes are lower with lawyers. If I knew my doctor was relying on LLMs for anything beyond the trivial (RAGS or not), I'd lose a lot of trust in that doctor.
I am a fan of ML, but simplicity bias and the fact that hallucinations are an intrinsic feature of LLMs is problematic.
ML is absolutely appropriate and will be useful for finding new models in medicine, but it is dangerous and negligent to blindly use, even quantification is often not analytically sufficient in this area.
I saw a RAG demo from a startup that allows you to upload patient's medical docs, then the doctor can ask it questions like: > what's the patient's bp? even questions about drugs, histories, interactions, etc. The AI keeps in mind the patient's age and condition in its responses, when recommending things, etc. It reminded me of a time I was at the ER for a rib injury and could see my doctor Wikipedia'ing stuff - coul…
You would also need to load an enormous amount of precedential case law, at least in the US and other common law jurisdictions. Synthesizing case law into rules of law applicable to a specific case requires complex analysis that is frequently sensitive to details of the factual context, where LLMs' lack of common sense can lead it to make false conclusions, particularly in situations where the available, on-point case law is thin on the ground and as a result directly analogous cases are not available.
I don't see the utility at the current performance level of LLMs, though, as the OP article seems to confirm. LLMs may excel in restating or summarizing black letter or well-established law under narrow circumstances, but that's a vanishingly small percentage of the actual work involved in practicing law. Most cases are unremarkable, and the lawyers and judges involved do not need to conduct any research that would require something like consulting an AI assistant to resolve all the important questions. It's just routine, there's nothing special about any given DUI case, for example. Where actual research is required, the question is typically extremely nuanced, and that is precisely where LLMs tend to struggle the most to produce useful outputs. LLMs are also unlikely to identify such issues, because they are issues for which sufficient precedent does not exist and therefore the LLM will by definition have to engage in extrapolational, creative analysis rather than simply reproducing ideas or language from its training set.
Earlier quoted context omitted.
> It reminded me of a time I was at the ER for a rib injury and could see my doctor Wikipedia'ing stuff To be honest, I'm much more comfortable with a doctor looking things up on wikipedia than using LLMs. Same with lawyers, although the stakes are lower with lawyers. If I knew my doctor was relying on LLMs for anything beyond the trivial (RAGS or not), I'd lose a lot of trust in that doctor.
>> Same with lawyers, although the stakes are lower with lawyers. Doctors and lawyer appear to be using LLMs in fundamentally different ways. Doctors appear to use them as consultants. The LLM spits out an opinion and the Doctor decides whether to go with it or not. Doctors are still writing the drug prescriptions. Lawyers seem to be submitting LLM-generated text to courts without even editing it, which is like the D…
If a doctor wrote the exact prescription an LLM outputs, how would anyone other than the LLM provider know?
I saw a RAG demo from a startup that allows you to upload patient's medical docs, then the doctor can ask it questions like: > what's the patient's bp? even questions about drugs, histories, interactions, etc. The AI keeps in mind the patient's age and condition in its responses, when recommending things, etc. It reminded me of a time I was at the ER for a rib injury and could see my doctor Wikipedia'ing stuff - coul…
I don't know if I would even agree with that. Wikipedia doesn't invent/hallucinate answers when confused, and all claims can be traced back to a source. It has the possibility of fabricated information from malicious actors, but that seems like a step up from LLMs trained on random data (including fabrications) which also adds its own hallucinations.
Earlier quoted context omitted.
I've 100% found AI to be super helpful in learning a new programming language or refreshing on one I haven't used in a while. Hey how do I this thing in Gleam? What's Gleams equivalent of y? I turn it first instead of forums/stackoverflow/google now and would say I only need to turn to other sources less than maybe 5% of the time.
I think that is right. The sweat spot is twofold: 1) A replacement for general search on a topic where you have limited familiarity that can give you an answer for a concise question, or a starting point for more investigation or 2) For power-user use cases, where there already exists subject matter expertise, elaboration or extrapolation from a clear starting point to a clear end state, such as translation or contex…
Earlier quoted context omitted.
> It reminded me of a time I was at the ER for a rib injury and could see my doctor Wikipedia'ing stuff To be honest, I'm much more comfortable with a doctor looking things up on wikipedia than using LLMs. Same with lawyers, although the stakes are lower with lawyers. If I knew my doctor was relying on LLMs for anything beyond the trivial (RAGS or not), I'd lose a lot of trust in that doctor.
>> Same with lawyers, although the stakes are lower with lawyers. Doctors and lawyer appear to be using LLMs in fundamentally different ways. Doctors appear to use them as consultants. The LLM spits out an opinion and the Doctor decides whether to go with it or not. Doctors are still writing the drug prescriptions. Lawyers seem to be submitting LLM-generated text to courts without even editing it, which is like the D…
Luckily doctoring has the safeguard that you will need a professional to get drugs/treatments, but there isn't as much of a safety net for lawyering
I wonder if this "AI will replace your job" is like "AI will drive your car" in that where once something can solve 95% of the problem the general public assumes the last 5% will come very quickly. Rodney Brooks used to point out that self-driving was perceived by the public as happening very quickly, when he could show early examples in Germany from the 1950s. We all know this kind of AI has been in development a lo…