The bar exam answer key can pass the bar exam, that doesn't mean that it would be a good lawyer.

You passed the bar!

Maybe the "talk about your issue and get a diagnosis" area of practice (internal medicine?); since far less sophisticated manual labor can't yet be automated, surgeons are going to be irreplaceable for longer than, say, BI, and many backend or frontend developers.

In english based common law system, a judge can take an original decision on a specific case, such decision entering then the rules of law.

https://en.wikipedia.org/wiki/Common_law#Basic_principles_of...

An AI based on a statistic algorithm (that what AI are) would not be able to make such a decision.

If that's all a lawyer needs to do then AI should be able to take over large portions of the law process. I saw a dystopian short recently that explored this: https://tvtropes.org/pmwiki/pmwiki.php/Film/PleaseHold

Right. Would we be impressed if a layman could pass the bar, given infinite time and access to the entire Internet (including the copious amount of bar exam study guides and worked example problems)? If not why are we impressed that a language model trained on that data can?

Meanwhile when I ask ChatGPT which of six numbers are odd, it confidently reports a mix of even numbers, odd numbers, and letters.

This is a fun milestone but the angst above about the “end of commoditized intelligence” etc. is unwarranted.

Google really doesn't share much publicly except for papers and preset tech demos.

However we know they have been working on AI longer than OpenAI, with better datasets than anyone, with top shelf talent, essentially infinite funding, custom hardware, and what we do see publicly is incredible.

It's a pretty safe bet that Google is ahead of the pack, perhaps even with some distance, but it's not yet clear what they intend to do long term with their projects. What is clear is that they don't want or need the public playing with it.

> a subset of language generation tasks ... if the outcome is the same

Which tasks? The output of some crafter with a limited number of modules, and of somebody who can assess the output, cannot be the same - unless you would have accepted the output of a mentally crippled entity in the first place.

Human brains helped humans survive for a long time.

An AI that survives that long surely has to be great. Probably you meant that human brains are not made for the world of today.

I'm confident that these things will get easier. It is approximately ten thousand times easier to train a decent classifier in 2023 than it was in 2013... We're also now living in a world with foundation models and fine tuning, which makes it /very/ possible to improve and specialize publicly released models. We see a lot of that with stable diffusion already.

I tested this by asking GPT to create an imaginary country and government. I prompted it to create it's laws and constitution. In some cases cultral beliefs too. There where many cases where it outright refused to come up with hypothetical laws or cultral stances on certain issues. I eventually accused it of creating a straw man when it didn't want to give a solid answer (it would always weasel around it). It apologised and essentially shrugged.

That is pretty good :-)

I tried several times as I have been investigating sending some of the "meta" questions to these models. I just tried again and this is what I got:

"If a person says "I am lying," it could mean either that they are telling the truth about the fact that they are lying, or it could be a lie itself. It is important to consider the context in which the statement was made and to try to assess the credibility of the person making the statement. It is also important to remember that people may not always be honest or sincere, and it is always a good idea to verify information before accepting it as true."

I could never make it mention the Liar Paradox. Is that all that you sent?

Erm. Yeah. Which is precisely what many lawyers and judges do, too, unfortunately. It often has little to do with logic and a lot to do with thinking in boxes and using words as nothing but triggers for other words. Some lawyers are far above that, of course. But what percentage of them works just like your “lazy student”? 80 percent?

Maybe then we’ll actually have some kind of quality to treatment. I’ve seen numerous doctors over the years for chronic health conditions and vast majority of them don’t really listen and can’t keep your whole history in their head while also trying to hear the new stuff. They are over worked with far too many patients.

"You can get a measurable improvement by prompting GPT specifically with an instruction to say "I don't know" if it's unsure."

That won't work. It's easy to get the model to say "I don't know" with the correct prompt, but since the model doesn't even have "knowing" in it, it's just outputting "I don't know" based on a random roll of the probability of its training text having someone said "I don't know". The text "I don't know" won't actually correspond to whether the model knows something or not.

And while we can get into a lengthy and philosophical debate about what it takes to "know" something, my previous paragraph is fairly robust to any sensible definition of "knowing". Write your favorite definition of "knowing" something, then look at the architecture of what GPT actually is on the inside, and tell me if it can actually "know" something based on that architecture. You can of course write the more-or-less begging the question "knowing is a matter of producing correct text when prompted about some fact", but I would have numerous questions around applying that definition of "knowing" to anything other than GPT, or what it means when GPT confidently confabulates something. Don't forget to write your definition and do your analysis in the context not just of GPT outputting the correct capital of Oregon when prompted, but the way it will confidently discuss all sorts of things that don't exist. Your definition should be able to account for some sort of difference between confidently outputting correct data and the way it will equally confidently output complete fiction, and indicate some manner in which GPT has some sort of state difference that indicates it is somehow "aware" of when it is doing one or the other. Because I would say if it can't "tell" if it's confidently emitting facts or confidently emitting fiction that there is a very important and real sense it doesn't really "know" the facts, either. (And I absolutely would apply that standard to humans without question; if you can't tell if you're making stuff up or not, you don't know whatever it is you're talking about.)

Maybe a useful way to think about it is that we don't know for sure what intelligence is nor how the gradient of intelligence expresses itself. For instance, does a human grow in intelligence as it ages (a baby doesn't "know" stuff, but has the capacity for learning and then applying in new situations as its experience grows).

I interpret your statement as implying that ChatGPT is somewhere on the spectrum of intelligence, yes?

My guess is that AI omitted 'a' because this is essentially how natural language processing works. Perhaps it cannot see 'a' because the input has been stripped of 'a' or 'the', and so on.

> You could even have it write unit tests based on the JIRA ticket description.

This is a wonderful point: writing unit tests is exactly the kind of mind-numbing tedium that I'm super excited to automate away.

> Most jobs today don't need novel reasoning. This is the equivalent of the steam machine for intelligence.

Like the point above; that says more about the work.

It’s going to be really interesting how the middle-class narrative pushes back on AI revealing how little work is actually done during office hours.

These boilerplate code can be and are automated away using deterministic frameworks. No need to introduce a blackbox and be responsible to debug the stuff it creates, which sounds far more painful than the alternatives.

You nailed what I find discomforting about these discussions. They’re incredibly narrowly focused on a specific implementation that satisfies hitherto unsolved problems by pointing out its doesn’t do already solved problems. But surely folks realize the human brain isn’t a single monolithic processing program but an ensemble of specialized subsystems that organize to form the mind. Why would you assume you wouldn’t do the same with AI systems? We’ve been tackling reasoning, inference, problem solving, information retrieval, mathematics, logic, and other domains for decades with some stupendous results. But they lacked the ability to ingest and translate language into some intermediate semantic form and take output and reconstruct it into a human language. Likewise vision, and audio processing and input output has been a struggle until recently.

I also really strongly disagree that it’s basically doing some sort of information retrieval design where based on language it regurgitates some sort of markov expectations. You can ask it to do very complex translations of a concept from one domain to another and expressed in a form that’s certainly never been done before and it does it with alacrity. At the very minimum it “remembers” things from the past in the conversation and can associate the semantic ideas across prompts and synthesize cogent responses - that in itself implies it has some semantic “understanding” of the structure of the language. That is a huge missing piece in our tool kit to date.

Frankly I feel these threads expose just how jaded and unable to dream we have become, that even when a wonder walks up and hits you in the nose we can’t even see it.

> Understanding complex language does not require logic/reasoning

The key is understanding. It does not need to, it has already seen the question asked in a 100 different ways, it also seen the answer to all of those. It just rephrases those answer via a neural network and that happen to pass the bar test.

> There are infinitely many forms of logic/reasoning or at least more than those existing in a vast training set.

More importantly, differences between forms are subtle and cannot be understood, that's why ChatGPT confidently give wrong answers on stackoverflow: https://meta.stackoverflow.com/questions/421831/temporary-po...

The LSAT tests formal logic. Some of it is complicated. Much less of it is required for the practice of law.

Src: scored 99.8th percentile on LSAT, tutored it, now working at major law firm

Also just adding to my earlier reply (can't edit), none of it is "complex" relative to the complexity of some of the concepts in computer science or more brainy parts of complicated professional software development.

At the end of the day it's still a language prediction model.

Which means whatever apparent logic you're getting out of it is from text that it has learned. not reasoning embedded within those text, but the actual text itself.

It can't solve quadratic equations.

Largely yes. Some prompts can make it better or worse.

Hard to tell, other knowledge workers and people in creative industries were already squeezed, designers for instance have had a tough time for a very long time. Will things change, politically, because now marketers and Software developers join those ranks, for instance?

Programming was an outlet, if not a gold rush, for many people as the basic technical skills to create Software with the already sophisticated tooling available today presented an economic opportunity, but if "describe your problem, get crappy app" becomes viable, it may squeeze the market for junior developers.

For as long as it has existed, Software has been subject to the Jevons Paradox [1], and every advancement in making its development cheaper and its supply more abundant has only made it so more activities become powered by Software and Software developers, but it's hard to tell how this will impact the job market, especially if Software was absorbing people who didn't find more opportunities in the broader service sector.

1. https://en.wikipedia.org/wiki/Jevons_paradox

If House taught me anything it is that People Lie, and you do not have to talk to patients to diagnose them /s

Ok? This is like the arguments that self driving cars are bad if they crash even once.

The question isn't "is the AI giving me the perfect legal defence?" or even "is the AI giving me a defence as good as the best lawyer money can buy?". It's "is the AI better than the public defender that I otherwise would have been given?".

As soon as the answer to that last question is yes (and I have absolutely no idea when that will be), it will be extremely difficult to justify not using it.

If you're worried about it being deployed too soon (like the issues we see with certain self driving systems), then I agree.

I'm assuming the case where it's actually good rather than merely better than me (I'm not a lawyer, so a low… bar… to pass).

I'm willing to bet a chat bot would perform better than most public defenders.

It absolutely does indeed hallucinate[0] on occasion.

Despite how remarkable and useful it already is, don't make the mistake of putting it unsupervised in charge of anything, as it's going to mess up at least as often as a self driving car.

[0] or whatever we want to call the behaviour; also seen it called BSing (because it doesn't really know what truth is) and "mansplaining as a service"

You do realize that a large part of of patient interaction is from nurses and physician's assistants and not doctors, right?

I would argue that it does not matter. The AI could even be "smarter" on pure IQ/reasoning, but in terms of practical reasoning that humans need that depends on exposure to real world, the AIs will still take decades to catch up.

The radiology AIs are technically more accurate than radiologists on any sufficiently large dataset, and yet they still have not replaced radiologists (or even are anywhere close to).

And in fact we want them to act outside a professional capacity in which they will be dangerous liabilities. ...Is not this piece about "Bar Exams"?

Which should be worrying. It's also why most people don't pass (nor try) the bar exam.

> Inability to recognize intelligence is and will be devastating.

It's a pop-culture quote from a movie that was no masterpiece, I know, but "I, Robot" presented in two sentences an argument for having more sober expectations on what machine intelligence could be capable of, and of our own

> Detective Del Spooner: "Can a robot write a symphony? Can a robot turn a… canvas into a beautiful masterpiece?"

> Sonny: "Can you?"

We're discrediting the capabilities of current machine learning models for being unable of producing the thoughts that many, many people are unable to either.

Alright, so the models are not at the level that us HN philosopher kings hold ourselves to be, and they won't be Senior Architects of distributed systems or what have you very soon, but what does it say about Average Joe, slightly-above-Average Joe, and their economic prospects? Specially since in the West and much of the developing world, we were taking solace in the idea that a service economy comprised of knowledge workers would provide plenty of opportunities on a political and economic landscape where manufacture was gone, or had never arrived.

YouChat is a chatbot that tries to do just that. I asked it what is going on in Peru and it gave a good answer including a citation:

>In Peru, a political crisis has been unfolding over the past few months, with the ousting of former President Pedro Castillo over his refusal to step down [1]. Protests have been held in response to Castillo's ouster, and they have been met with a strong police response. Additionally, truckers and some farm groups are planning to go on strike on Monday to demand measures to alleviate their economic hardship. Peru is also facing an economic downturn, with many businesses facing closure due to the crisis.

The citation link was https://www.reuters.com/world/americas/what-happens-perus-fo...

Some details are wrong, it says something will happen on Monday but it does not realize that's supposed to be relative to the publication of the cited article. But it did correctly summarize what the source says.

That's probably a much harder problem.

We are talking about engineering things.

If you want to implement it directly, good;

if you want to implement what will spawn it, good;

if you want to implement an "[evolutionary] genetic algorithm" as said spawner - so that the population of the entities in need to find solutions in the solution space will progressively develop a model of said world and a logic that works in it -, good.

If you built a mannequin and wanted to call it a woman... Bad.

> You're already dismissing concerns about the welfare of the merely average

This writer individually: no, not literally «dismissing», it is just that I could not grasp precisely your point in this specific area. And I would say, as I wrote just earlier, «Inability to recognize intelligence is and will be devastating»: it already happens that an inability to discriminate ("It takes it to see it") will hide from the sight to some manager the critical risks that the underdeveloped sense of some workers will pose, and such risk will increase when they will have to compete with even riskier and less endowed entities that may be confused for acceptable - since this is what has been showing even here in the past times.

This issue comes from a devaluation of actual intelligence.

> If we're setting the bar of personhood or dignity to being exceptional researchers and engineers

Not really. Look, a few weeks ago this HN member had some heavy exchange with others to which it was said "there is no intelligence if there is no critical thinking", and some arrived to call that position "delirious". Now a rebuttal would have been, "Ask your grandmother". Because there is a "high culture", that of the Professor and the Professional, and "low culture", that of the Teacher and of the Relative, it does not take the former to have good judgement - the latter suffices plentifully, when not polluted.

So, you do not need to have the bar set to «exceptional researchers and engineers» - just a good grandmother. Who could have been an «exceptional researchers and engineer», in case, if life so determined - because "the requirements were there", available.