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What happens when people don't understand how AI works

theatlantic.com

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Re: What happens when people don't understand how AI works

#211

Post by spacemadness »

duxup wrote: post #141
kelseyfrog wrote: post #7

LLMs are divinatory instruments, our era's oracle, minus the incense and theatrics. If we were honest, we'd admit that "artificial intelligence" is just a modern gloss on a very old instinct: to consult a higher-order text generator and search for wisdom in the obscure. They tick all the boxes: oblique meaning, a semiotic field, the illusion of hidden knowledge, and a ritual interface. The only reason we don't call i…

The terminology is so confusing in AI right now. I use LLMs, I enjoy them, I'm more productive with them. Then I go read a blog from some AI devs and they use terms like "thinking" or similar terms. I always have to ask "We're still s stringing words together with math right? Not really thinking right?" The answer is always yes ... but then they go back to using their wonky terms.

Or saying they’re close to AGI because LLM behavior is indistinguishable from thinking to them. Especially here on HN I see “what’s the difference?” arguments all the time. It looks like it to me so it must be it. QED.

Re: What happens when people don't understand how AI works

#212

Post by baq »

duxup wrote: post #141
kelseyfrog wrote: post #7

LLMs are divinatory instruments, our era's oracle, minus the incense and theatrics. If we were honest, we'd admit that "artificial intelligence" is just a modern gloss on a very old instinct: to consult a higher-order text generator and search for wisdom in the obscure. They tick all the boxes: oblique meaning, a semiotic field, the illusion of hidden knowledge, and a ritual interface. The only reason we don't call i…

The terminology is so confusing in AI right now. I use LLMs, I enjoy them, I'm more productive with them. Then I go read a blog from some AI devs and they use terms like "thinking" or similar terms. I always have to ask "We're still s stringing words together with math right? Not really thinking right?" The answer is always yes ... but then they go back to using their wonky terms.

I can write or speak to a computer and it understands most of the time. It can even answer some questions correctly, much more so if given material to search in without being very specific.

That’s… new. If it’s just a magic trick, it’s a damn good one. It was hard sci-fi 3 years ago.

Re: What happens when people don't understand how AI works

#213

Post by diffeomorphism »

725686 wrote: post #197
kelseyfrog wrote: post #54

Earlier quoted context omitted.

Sure, some people stepped up to the Oracle and asked how to conquer Persia. Others probably asked where they left their sandals. The quality of the question doesn't change the structure of the act. You presented clear, factual queries. Great. But even there, all the components are still in play: you asked a question into a black box, received a symbolic-seeming response, evaluated its truth post hoc, and interpreted…

"how to conquer Persia" and "what is the name of the small fibers which form a bird’s feather" are very different kinds of questions. There is no one right answer for the first. That is divination. The second is just information retrieval.

Which the LLM then does not do and instead makes up likely text.

As prominent examples look at the news stories about lawyers citing nonexistent cases or publications.

People think that LLMs do information retrieval, but they don't. That is what makes them harmful in education contexts.

Re: What happens when people don't understand how AI works

#214

Post by Terr_ »

duxup wrote: post #141
kelseyfrog wrote: post #7

LLMs are divinatory instruments, our era's oracle, minus the incense and theatrics. If we were honest, we'd admit that "artificial intelligence" is just a modern gloss on a very old instinct: to consult a higher-order text generator and search for wisdom in the obscure. They tick all the boxes: oblique meaning, a semiotic field, the illusion of hidden knowledge, and a ritual interface. The only reason we don't call i…

The terminology is so confusing in AI right now. I use LLMs, I enjoy them, I'm more productive with them. Then I go read a blog from some AI devs and they use terms like "thinking" or similar terms. I always have to ask "We're still s stringing words together with math right? Not really thinking right?" The answer is always yes ... but then they go back to using their wonky terms.

Sometimes we anthropomorphize complex systems and it's not really a problem, like how water "tries" to flow downhill, or the printer "wants" cyan ink. It's how we signal there's sufficient complexity (or unknowns) that can be ignored or deferred.

The problem arises when we apply this intuition to things where too many people in the audience might take it literally.

Re: What happens when people don't understand how AI works

#215

Post by baq »

mdaniel wrote: post #184
duxup wrote: post #141

Earlier quoted context omitted.

The terminology is so confusing in AI right now. I use LLMs, I enjoy them, I'm more productive with them. Then I go read a blog from some AI devs and they use terms like "thinking" or similar terms. I always have to ask "We're still s stringing words together with math right? Not really thinking right?" The answer is always yes ... but then they go back to using their wonky terms.

I wanted to fight the "hallucinating" versus "confabulating" delineation but was told "it's a term of art, sit back down"

State of the art is such they’re constantly hallucinating new terms for old concepts.

Language evolves, but we should guide it. Instead they just pick up whatever sticks and run with it.

Re: What happens when people don't understand how AI works

#216

Post by kenjackson »

jhedwards wrote: post #196
kenjackson wrote: post #171

Earlier quoted context omitted.

This is really over indexing on language for LLMs. It’s about taking input and generating output. Humans use different types of senses as their input, LLMs use text. What makes thinking an interesting form of output is that it processes the input in some non-trivial way to be able to do an assortment of different tasks. But that’s it. There may be other forms of intelligence that have other “senses” who deem our abil…

Sure, but my whole point is that humans are _not_ passive input/output systems, we have an active biological system that uses an input/output system as a tool for coordinating with the environment. Thinking is part of the active system, and serves as an input to the language apparatus, and my point is that there is no corollary for that when talking about LLMs.

The environment is a place where inputs exist and where outputs go. Coordination of the environment in real time is something that LLMs don’t do much of today although I’d argue that the web search they know perform is the first step.

Re: What happens when people don't understand how AI works

#217

Post by iainctduncan »

spacemadness wrote: post #211
duxup wrote: post #141

Earlier quoted context omitted.

The terminology is so confusing in AI right now. I use LLMs, I enjoy them, I'm more productive with them. Then I go read a blog from some AI devs and they use terms like "thinking" or similar terms. I always have to ask "We're still s stringing words together with math right? Not really thinking right?" The answer is always yes ... but then they go back to using their wonky terms.

Or saying they’re close to AGI because LLM behavior is indistinguishable from thinking to them. Especially here on HN I see “what’s the difference?” arguments all the time. It looks like it to me so it must be it. QED.

or rather "while I have never studied psychology, cognition, or philosophy, I can see no difference, so clearly they are thinking!"

makes the baby jesus cry

Re: What happens when people don't understand how AI works

#218

Post by browningstreet »

baq wrote: post #215
mdaniel wrote: post #184

Earlier quoted context omitted.

I wanted to fight the "hallucinating" versus "confabulating" delineation but was told "it's a term of art, sit back down"

State of the art is such they’re constantly hallucinating new terms for old concepts. Language evolves, but we should guide it. Instead they just pick up whatever sticks and run with it.

These word choices are about impact and in-group buy-in. They're prescriptive cult-iness, not descriptive communication.

Re: What happens when people don't understand how AI works

#219

Post by mjburgess »

throwawaymaths wrote: post #209
827a wrote: post #185

Earlier quoted context omitted.

> I cant see how this doesn't describe, abstractly, human cognition. now, maybe llms are not fully capable of the breadth of human cognition But, I can fire back with: You're making the same fallacy you correctly assert the article as making. When I see how a CPU's ALU adds two numbers together, it looks strikingly similar to how I add two numbers together in my head. I can't see how the ALU's internal logic doesn't…

do they matter in a practical sense? an LLM can write a structured essay better than most undergrads. and as for measuring "smart", we throw that word around a lot. a dog is smart in a human way for being able to fetch one of 30 objects based on name or to drive a car (yes, dogs can drive), the bar for "smart" is pretty low, claiming llms are not smart is just prejudice.

You are assuming that because we measure an undergrad's ability to critical think with undergrad essays, that is a valid test for the LLM's capacity to think -- it isnt. This measures only, extremely narrowly, the LLM's capacity to produce undergrad essays.

Society doesnt require undergrad essays. Nor does it require yet another webserver, iot script, or weekend hobby project. Society has all of those things already, hence the ability to train LLMs to produce them.

"Society", the economy, etc. are operating under competitive optimisation processes -- so that what is valuable, on the margin, is what isn't readily produced. What is readily produced, has been produced, is being produced, and so on. Solved problems are solved problems. Intelligence is the capacity of animals to operate "on the margin" -- that's why we have it:

Intelligence is a process of rapid adaption to novel circumstances, it is not, unlike puzzle-solvers like to claim, the solution to puzzles. Once a puzzle is solved so there are historical exemplars of its solution, it no longer requires intelligence to solve it -- hence using an LLM. (In this sense computer science is the art of removing intelligence from the solving of unsolved and unposed puzzles).

LLMs surface "solved problems" more readily than search engines. There's no evidence, and plenty against, that they provide the value of intelligence -- their ability to advance one's capabilities under compeititon from others, is literally zero -- since all players in the economic (, social, etc.) game have access to the LLM.

The LLM itself, in this sense, not only has no intelligence, but doesnt even show up in intelligent processes that we follow. It's washed out immediately -- it removes from our task lists, some "tasks that require intelligence", leaving the remainder for our actual intelligence to engage with.

Re: What happens when people don't understand how AI works

#220

Post by 827a »

throwawaymaths wrote: post #209
827a wrote: post #185

Earlier quoted context omitted.

> I cant see how this doesn't describe, abstractly, human cognition. now, maybe llms are not fully capable of the breadth of human cognition But, I can fire back with: You're making the same fallacy you correctly assert the article as making. When I see how a CPU's ALU adds two numbers together, it looks strikingly similar to how I add two numbers together in my head. I can't see how the ALU's internal logic doesn't…

do they matter in a practical sense? an LLM can write a structured essay better than most undergrads. and as for measuring "smart", we throw that word around a lot. a dog is smart in a human way for being able to fetch one of 30 objects based on name or to drive a car (yes, dogs can drive), the bar for "smart" is pretty low, claiming llms are not smart is just prejudice.

Well; many LLMs can compose a structured essay better than most undergrounds, yet most also struggle with basic addition. E.g. Gemma-3-4B:

add 1 and 1

google/gemma-3-4b 1 + 1 = 2

add four to that

google/gemma-3-4b 1 + 1 + 1 + 1 = 4

So, 1 + 1 + 1 + 1 + 4 = 8

Of course, smarter, billion dollar LLMs can do that. But, they aren't able to fetch one of 30 objects based on name, nor can they drive a car. They're often super-important components of much larger systems that are, at the very least, getting really close to being able to do these things if not able to already.

It should be worldview-changing to realize that writing a graduate-level research essay is, in some ways, easier than adding 4 to 2. Its just not easier for humans or ALUs. It turns out, intelligence is a multi-dimensional spectrum, and words like "smart" are kinda un-smart to use when describing entities who vie for a place on it.

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