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Comment by somewhereoutth | Hacker News Reader

I think the term 'Intelligence' is what is causing the problem. If something like 'statistical modelling' or 'quasi-stochastic information compression' was used instead there would be much less hot air.

For example, in Real Time Analytics, there is something called a 'sketch', which though clever statistical techniques allows approximations of such things like top 10, average etc, without having to recalculate from the whole dataset each time of asking. Nobody claims this has anything to do with intelligence, artifical or otherwise.

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My impression is that the vast majority of people who are currently engaged in the “discourse” surrounding AI do not have the technical background to make this distinction. In my opinion, there’s an element of “the man behind the curtain” which is being unethically leveraged by AI companies to drive sales and hype.

Plus, there seems to be a chronic conflation of "capable of configuring" and "fundamentally understanding the technology".

I agree and there is an enormous moral hazard to the latter. Just looking at what Hinton has been discussing post G, and you see ideological support for a narrow model, shameless anthropomorphization of LLM behavior, and downplaying of "hallucinations" (which I'd rather simply call what it is, which is lying).

The moral hazard (for sure not new) is that those most equipped to call out the overplaying of the technology's abilities are also those most personally incented (via fame for their creation), or commercially incented (as you mentioned) to drive sales and hype.

> which I'd rather simply call what it is, which is lying

I like the term "bullshitting" as it implies it acts like it knows, but doesn't.

I can't stand it when they call it "hallucinating", as it instead might imply the problem is with the interpretation of the sensory input. This term might be more appropriate to describe adversarial attacks executed through information input.

"which I'd rather simply call what it is, which is lying"

"I like the term "bullshitting" as it implies it acts like it knows, but doesn't."

It's not "lying" or "bullshitting". It's working as designed. It's not a repository of truth; just long-form autofill.

It's not being sold as long-form autofill. It's being sold as something which will respond to queries, and there is an expectation that the information it replies with should have some accuracy.

I am not in disagreement with your generalization of how it functions or that it lacks empirical knowledge. Some responses are accurate, some are not. It will always give a response but does not always produce a disclaimer saying that the response might have been inaccurate.

So, in criticism of the existing nomenclature used to describe this phenomena (hallucination), I simply suggested something more appropriate.

I agree that it's being positioned deceptively.

Today, it is just a novelty.

I think “malfunctioning” is the correct term you are looking for. Lying and Bullshitting and Hallucinating anthropomorphises the software. It is simply not functioning as advertised (not intended).

"Malfunctioning" isn't really accurate, either—because the common usage of that term isn't "not functioning as advertised", not in this world where salespeople will say literally anything to get someone to buy their product. It's "not functioning as designed".

"Hallucinations" are 100% an LLM functioning as designed. They are every bit as valid as any other output. LLMs have no concept of truth, no model of the world, no way even in theory to determine the validity of any particular statement they output.

The problem isn't the term "hallucinations", so much as it is the idea that anything they produce is not a hallucination.

I totally agree with this. I like the term "criti-hype". To me, the NYT interview with Hinton seems so obviously calculated for this kind of effect. What is much more worrisome to me than any of the supposed abilities of recent ML models is the fact that the average person just... doesn't seem to pick up on this kind of thing.

Although, I wouldn't personally say that it's "lying", "bullshitting", or anything else. That's just more anthropomorphization. It's "wrong" or "incorrect". A mathematical model, a clock, a map: these can all be "wrong" or "incorrect". You might say they were lying to you, but it would be for comedic effect. In this case, there are (again!) enough people who lack the ability to make the technical distinction that I think it's important we avoid any kind of anthropomorphization of any ML model to avoid confusion.

Maybe a more precise (albeit informal) term would be "freestyling" or "improvising" :)

Same thing happened with VMs, "the cloud" and containers... Hapless CIOs and senior technical advisors around the world were convinced all their problems would be solved if they'd just sign a contract with <arbitrary vendor>.

And their on the ground technical people would tell them "this ain't it" but would be shushed to tell a story to CEOs and shareholders.

> Same thing happened with VMs, "the cloud" and containers... Hapless CIOs and senior technical advisors around the world were convinced all their problems would be solved if they'd just sign a contract with <arbitrary vendor>.

Pinning this on the phrase "the cloud" is a mistake, it's part of a much broader trend of using specialist contractors for things instead of doing everything in house. If you could somehow magically go back in time and prevent "the cloud" or any other equivalent phrase from existing, the same trend of companies hiring other companies to do the work they don't care to specialize in would still exist.

From the perspective of... an insurance company.. why shouldn't they contract another company to handle the servers? They already hire another company to hire janitorial work, building construction and maintenance, human resources, running their cafeteria, call centers, etc, etc... The computer stuff seems special to us because we're tech workers and this is a tech forum, but really it isn't special and it happens in virtually all aspects of doing business. The trend doesn't exist because of the buzzword, the buzzword exists because of the trend. If the buzzword didn't exist, a new one would be invented immediately, because language is a tool for conveying ideas and people make new tools on the fly whenever we find ourselves needing one. Ideas don't come from words; words come from ideas.

Could you expand on why you don't believe "intelligence" is an appropriate word?

I guess I don't understand why a system built on "statistical modelling" would be incompatible with a system that has properties of "intelligence".

We use "intelligence" fairly loosely already. Significantly less intellectually capable animals are often referred to as "intelligent" – pigs, dogs, etc. Plus, the field of research applied "statistical modelling" belongs to literally is artificial "intelligence". I think it's fine (perhaps even appropriate) to refer to artificial systems which perform intellectual tasks as forms of intelligence.

> For example, in Real Time Analytics, there is something called a 'sketch', which though clever statistical techniques allows approximations of such things like top 10, average etc

This is a very narrow and weak example of artificial intelligence in my opinion.

I don't think the issue here is the word "intelligence", it's more that people tend to use human intelligence as the benchmark for what it means to be "intelligent". So when someone says something like "ChatGPT is intelligent" there is a subset of people who get annoyed because they think that person is directly equating ChatGPT's abilities with human-level intelligence.

> Could you expand on why you don't believe "intelligence" is an appropriate word?

The problem with the word "intelligence" is that it's very poorly defined, and what people mean by it varies a tremendous amount.

But I agree that I don't think the word itself is what leads people to be very, very nervous about this tech.

Intelligence implies agency, self awareness, thoughts and feelings - none of which has anything to do with the current crop of word generators.

Yeah, 'tabooing' the word intelligence could help correct hype, the problem is it could overcorrect: just because you decide to taboo the word, doesn't mean that current-or-future AI isn't "intelligent". Words don't have that power, unfortunately, to make a system "intelligent"--or not.

One limitation of “intelligence” is that it isn’t task-specific. There’s no IQ or ‘g’ for machines (yet) and their performance varies along many dimensions.

We should see how well a machine does on each task we care about, using task-specific benchmarks and testing. This avoids a lot of fuzzy thinking about potential.

I think it’s reasonable to use the word intelligence, if you define intelligence as something like “a system’s ability to take in information and use that information rationally to decide what action to take to meet a goal”, which seems like a good definition to me. It might be tempting to define it in a way that only includes what humans do but I don’t think that’s a good general definition

Yep. I precision about intelligence versus sentience is keeping the waters muddy.

We (the set of English speakers at large) don't have a universal definition of "intelligence" because we have only a loose idea about what it is.

That problem is even worse with "sentience", where we basically don't know what it is beyond the vaguest hint.

We don’t have perfect definitions for either word, but I’m comfortable with intelligence meaning something like goal seeking or reasoning, and sentience meaning something like self-awareness or identity.

The fact that we can’t perfectly define either “blue” or “green” does not mean that blue and green are semantically interchangeable.

What makes a behavior rational? Linear models take in information and use that information to decide what action to take to meet a goal. When you are fitting a best line, I suppose that could be rational, or it isn’t, it depends on the usage. I find it hard to justify calling one thing “intelligent” and the other thing not.

That definition includes all computers. Is that your intent?

Not really, because computers on their own aren't really agents that optimise their actions towards a goal. But they can definitely be programmed to do that

I guess you could argue that following machine code instructions is as much of a goal as predicting the next token though, except it's not quite the same as there's a clear right way to follow the instructions but predicting tokens is more... fuzzy?

OK, then I'm genuinely confused by your definition...

I guess I confused myself a bit as well there

Edit: I still think my point stands but my definition might not be worded well

I think the Legg&Hutter definition "Intelligence measures an agent’s ability to achieve goals in a wide range of environments" [1] is quite relevant for this issue - once we consider not a technique for a specific task, but a single system adapted for a variety of tasks and which (and this is the key part!) we also expect to perform well on a new task handed over to it, then that does mean that we are trying to build systems that are explicitly "more intelligent" according to this definition.

[1] 2007 Shane Legg, Marcus Hutter A Collection of Definitions of Intelligence https://arxiv.org/abs/0706.3639

Yeah, the working definition I use, which is a simplification of the academic definition, is "second order solutions/algorithms", where rather than a program defining a solution to a problem given some set of arguments, you have a program that takes a problem definition as input, and produces a process that can solve many instances of that problem.

That ends up being very different from the "AI is anything a computer can't do yet" pop definition, because it includes everything from SAT solvers, propositional logic engines, and Bayesian network analyzers, to the more bleeding edge deep learning stuff.

The word 'intelligence' not being used would last about 5 minutes until somebody else had the idea to call these systems intelligent. Therefore word itself cannot be the root of it. The perception of these systems being intelligent is trivially derived from the nature and capabilities of the systems, it isn't some unfortunate fluke of language that foisted these comparisons on us.

Indeed no fluke. Probably sci-fi led the way and captured the public imagination, then it was an easy meme for researchers to latch on to as they try to gain notariaty, funding etc for their work.

The nature and capabilities of these systems are a very long way from anything else we consider intelligence. If they didn't contain a 'neural net' I suspect the connection would not really occur to anyone - anymore than people consider Google search to be intelligent.

> 'quasi-stochastic information compression'

Isn't that what we humans do? We try to find patterns to discover underlying mechanisms. That's information compression.

The difference is that people have been fed a constant diet of AI will rise up and destroy humanity for decades now in popular media.

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