It’s not making Turing test obsolete. It was obvious from day 1 that Turing test is not an intelligence test. You could simply create a sufficiently big dictionary of “if human says X respond with Y” and it would fool any person that its talking with a human with 0 intelligence behind it. Turing test was always about checking how good a program is at chatting. If you want to test something else you have to come up with other test. If you want to test chat bots you will still use Turing test.
Sounds to me like that sufficiently large dictionary would be intelligent. Like, a dictionary that can produce the correct response to every thing said sounds like a system that can produce the correct response to any thing said. Like, that system could advise you on your career or invent machines or whatever.
No, a dictionary is not intelligent. A dictionary simply matches one text to another. A HashMap is not intelligent. But it can fool a human that it is.
Yes, but you could argue that human brain is a large pattern matcher with a dictionary. What separates human intelligence from machine intelligence?
The question is not if something is a patter matcher or not. The question is how this matching is done. There are ways we consider intelligent and ways that are not. Human brain is generally considered intelligent, some algorithms using heuristics or machine learning would be considered artificial intelligence, a hash map matching string A to string B is not in any way intelligent. But all this methods can produce the same results so it’s impossible to determine if something is intelligent or not without looking inside the black box.
Yet language and abstraction are the core of intelligence. You cannot have intelligence without 2 way communication, and if anything, your brain contains exactly that dictionary you describe. Ask any verbal autistic person, and 90% of their conversations are scripted to a fault. However, there’s another component to intelligence that the Turing Test just scrapes against. I’m not philosophical enough to identify it, but it seems like the turing test is looking for lightning by listening for rumbling that might mean thunder.
If you want to get philosophical the truth it we don’t know what intelligence is and there’s no way to identify it in a black box. We may say that something behaves intelligently or not but we will never be able say if it’s really intelligent. Turing test check if a program is able to chat intelligently. We can come up with a test for solving math intelligently or driving car intelligently but we will never have a test for what most people understand as intelligence.
This is what it comes down to. Until we agree on a testable definition of “intelligence” (or sentience, sapience, consciousness or just about any descriptor of human thought), it’s not really science. Even in nature, what we might consider intelligence manifests in different organisms in different ways.
We could assume that when people say intelligence they mean human-like intelligence. That might be narrow enough to test, but you’d probably still end up failing some humans and passing some trained models
It’s not that it’s not science. Different sciences simply define intelligence in different ways. In psychology it’s mostly the ability to solve problems by reasoning so ‘human like’ intelligence. They don’t care that computers can solve the same problems without reasoning (by brute force for example) because they don’t study computers. In computer science it’s more fuzzy but pretty much boils down to algorithms solving problems by using some sort of insights that are not simple step-by-step instructions. The problem is that with general AI we’re trying to unify those definitions but when you do this both lose it’s meanings.
You’re right, it’s very much context dependent, and I appreciate your incite on how this clash between psychology and computer science muddies the terms. As a CS guy myself who’s just dipping my toes into NN’s, I lean toward the psychology definition, where intelligence is measured by behavior.
In an artificial neural network, the algorithms that wrangle data and build a model aren’t really what makes the decisions, they just build out the “body” (model, generator functions) and “environment” (data format), so to speak. If anything that code is more comparable to DNA than any state of mind. Training on data is where the knowledge comes from, and by making connections the model can “reason” a good answer with the correlations it found. Those processes are vague enough that I don’t feel comfortable calling them algorithms, though. It’s pretty divorced from cold, hard code.
So would a book could be considered intelligent if it was large enough to contain the answer to any possible question? Or maybe the search tool that simply matches your input to the output the book provides, would that be intelligence?
To me, something can’t be considered intelligent if it lacks the ability to learn.
The idea that “a computer would deserve to be called intelligent if it could deceive a human into believing that it was human” was already obsolete 50 years ago with ELIZA. Clever though it was, examining the source code made it clear that it did not deserve to be called intelligent any more than does today’s average toaster.
And then more recently, the ever-evolving chatbots have made it increasingly difficult to administer a meaningful Turing test over the past 30 years as well. It requires care and expertise. It can’t be automated, and it can’t be done by the average person who hasn’t been specifically trained in it. They’re much better at fooling people who’ve never talked to one before, but I think someone with lots of practice identifying the bots of 2013 would still have not much trouble catching out those of today.
It cannot be automated or systematized because neural networks are the tool you use to defeat systems like that. If there’s a defined, objective test, a neural network can train for/on that test and ‘learn’ to ace it. It’s just what they do.
The only way to test for ‘true’ intelligence would be to perfectly define it first, such that when the NN aced the test that would prove intelligence. That is, IF you could perfectly define intelligence, doing so would more or less give you all the tools you needed to create it.
All these people claiming we already have general AI or even anything like it have put the cart so far before the horse.
I disagree with the “limitations” they ascribe to the Turing test - if anything, they’re implementation issues. For example:
For instance, any of the games played during the test are imitation games designed to test whether or not a machine can imitate a human. The evaluators make decisions solely based on the language or tone of messages they receive.
There’s absolutely no reason why the evaluators shouldn’t take the content of the messages into account, and use it to judge the reasoning ability of whoever they’re chatting with.
Voight-Kampff test maybe?
Imagine someone asked you “If Desk plus Love equals Fruit, why is turtle blue?”
AI will actually TRY to solve it.
Human nature would be to ask if the person asking the question is having a stroke or requires medical attention.So, I asked this to the three different conversation styles of Bing Chat.
The Precise style actually tried to solve it, came to the conclusion the question might be of philosophical nature, including some potential meanings, and asked for clarification.
The Balanced style told me basically the same as the other reply by admiralteal, that the question makes no sense and I should give more context if I actually want it answered.
The Creative style told me it didn’t understand the first part, but then answered the second part (the turtles being blue) seriously.
Would it be safe to say that all 3 answers would fail the test?
Not sure, I’m not familiar with the test, just figured I’d tell the results from asking the AI.
I think based on what you said about it
AI will actually TRY to solve it.
Human nature would be to ask if the person asking the question is having a stroke or requires medical attention.That the Balanced style didn’t fail, because while it didn’t ask about strokes or medical attention, it did point out I’m asking a nonsense question and refused to engage with it.
The Precise style did try to find an answer and the Creative style didn’t realize I’m fucking with it, so I do think based on the criteria they’d fail the test.
Though, honestly, I’d fail the test too. When asked such a question, I’d think there has to be an answer and it’s stupid of me not to see it and I’d look for it. I think the Precise style’s answer is very much where I’d end up.
Nope, ChatGPT tells you it is a nonsequitor and asks for more context or intention if the question is sincere.
You’re saying the test would work.
In 43+ years on this planet I’ve never HEARD someone seriously use “non sequitur” properly in a sentence.
Asking if the intention is sincere would be another flag given the circumstances (knowing they were being tested).Toss in a couple real questions like: “What is the 42nd digit of pi?”, “What is the square root of -i ?”, and you’d find the AI pretty quick.
Cool.
Both the phrases you’re calling out as clearly AI came from me. Not used by ChatGPT, just how I summarized its response. I wonder if this is the first time someone has brazenly accused me of being an AI bot?
LoL, no I took you at your word which was my mistake
“ChatGPT tells you” read to me like you attempted and got that response.
The Turing test has been obsolete for better than two decades. The premise of this article is incorrect.
Ironically GPT4 fails the turing test for having so wide knowledge about almost everything that you just know it’s not a human you’re talking to.
The problem with AI is that it does not understand anything. You can have a completely reasonable sounding conversation that is just full of stupidity and the AI does not know it because it does not no anything.
Another AI issue is it works until it does not and that failure can be rather severe and unexpected. Again because the AI knows nothing.
Seems like we need some test to address this. They are basically the same problem. Or maybe it is some training so that the AI can know what it does not know.
Define “understand” as you’re using it here? What exactly does the AI not do, that humans do, that comprises “understanding”?
Understanding the general sanity of some of their responses. Synthesizing new ideas. Having a larger context. AI tends to be idiot savants on one hand and really mediocre on the other.
You could argue that this is just a reflection of lack of training and scale but I wonder.
You will change my mind when I have had a machine interaction where the machine does not seem like an idiot.
Edit: AI people call the worst of these hallucinations but they are just nonsensical stuff that proves AI knows nothing and are just dumb correlation engines.
AI knows nothing and are just dumb correlation engines
Here’s a thought exercise, how do you “know”? How do you know your pet? LLMs like gpt can “know” about a dog in terms of words, because that’s what they “sense”, that’s how they interact with their “environment”. They understand words and how they relate to other words, basically words are their entire environment.
Now, can you describe how you know your dog without your senses, or anything derived from your senses? Remember, chemical receptors are “senses” too.
I remember reading about this awhile back but I don’t have the link on me: Did you know that people who were born blind but have their vision repaired years later don’t immediately know what “pointy” looks like? They never formed that correlation between the feeling of pointy and the visual of pointy the way that they could with the feeling and the word.
My point is, we’re correlation machines too
The Turing Test isn’t really intended to identify a computer – Turing’s problem wasn’t that we needed a way to identify computers.
At the time – well, and to some extent today – some people firmly felt that a computer could actually think, that that is something “special” that only humans can do.
It’s intended to support Turing’s argument for a behavioral approach to thinking – that if a computer can behave indistinguishably from a human that we agree thinks, then that should be the bar for what we talk about when talking about thinking.
There have been people since who have aimed to actually work towards such chatbot, but for Turing, this was just a hypothetical to support his argument.
https://en.wikipedia.org/wiki/Turing_test
The test was introduced by Turing in his 1950 paper “Computing Machinery and Intelligence” while working at the University of Manchester.[5] It opens with the words: “I propose to consider the question, ‘Can machines think?’” Because “thinking” is difficult to define, Turing chooses to “replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.”[6]
Turing did not intend for his idea to be used to test the intelligence of programs—he wanted to provide a clear and understandable example to aid in the discussion of the philosophy of artificial intelligence.[82] John McCarthy argues that we should not be surprised that a philosophical idea turns out to be useless for practical applications. He observes that the philosophy of AI is “unlikely to have any more effect on the practice of AI research than philosophy of science generally has on the practice of science.”[83][84]
The point of logic is to carry you when your emotions try to stop you from thinking.
Yes AI is scary. No, that doesn’t mean we get to through out our definition of AI in order to avoid recognizing its presence.
I’m reminded of the apocryphal Ghandi quote “first they ignore you, then they laugh at you, then they fight you, then you win.” It seems like the general zeitgeist is in between the laugh/fight stages for AI right now.
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To try to answer this question, a team of researchers has proposed a novel framework that works like a psychological study for software.
This is why the Turing Test may no longer be relevant, and there is a need for new evaluation methods that could effectively assess the intelligence of machines, according to the researchers.
During the Turing Test, evaluators play different games involving text-based communications with real humans and AI programs (machines or chatbots).
The same applies to AI as well, according to a study from Stanford University which suggests that machines that could self-reflect are more practical for human use.
“AI agents that can leverage prior experience and adapt well by efficiently exploring new or changing environments will lead to much more adaptive, flexible technologies, from household robotics to personalized learning tools,” Nick Haber, an assistant professor from Stanford University who was not involved in the current study, said.
It doesn’t tell us anything about what a system can do or understand, anything about whether it has established complex inner monologues or can engage in planning over abstract time horizons, which is key to human intelligence,” Mustafa Suleyman, an AI expert and founder of DeepAI, told Bloomberg.
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