221–230 of 321 posts
Earlier quoted context omitted.
Certainly they are big state machines, but is there any proof that we are not?
People ask this question like it's meaningful... is there any proof that we are? No. Then stop asking it as if it sheds light into the similarities between humans and machines... it doesn't and it's obfuscating to that extent.
This highlights one of the types of muddled thinking around LLMs. These tasks are used to test theory of mind because for people, language is a reliable representation of what type of thoughts are going on in the person's mind. In the case of an LLM the language generated doesn't have the same relationship to reality as it does for a person. What is being demonstrated in the article is that given billions of tokens o…
How do I know my thoughts aren't statistical noise?
Earlier quoted context omitted.
Defining what "knowing" is would be useful, yes, and analytic philosophers in epistemology do argue about this. One attribute that's classically part of the definition of "knowing" is that the thing which is known must be true. LLMs are pretty bad at this, but perhaps that can be fixed. But I would challenge you to imagine the situation the LLM is actually in. Do you understand Thai? If so, in the following, feel fre…
A follow up question: as a human doesn't start with "knowing" something either and first creates definitions for objects or words, which it then uses to build increasingly abstract concepts that we eventually classify as "knowledge" on the thing, is there anything that would stop LLMs from being able to do the same thing? I fully agree the capability is not there yet, but I can't say what would stop an appropriately…
The point, for this thread, is not whether or not Socrates was correct.
Rather, it’s a warning that we must not confidently assume we are anything like a machine.
We may have souls, we may be eternal, there may be something utterly immaterial at the heart of us.
As we strive to understand the inner-workings of machines that appear, at times, to be human-like, we ought not succumb to the temptation to think of ourselves as machine-like merely in order to convince ourselves (incorrectly) that we understand what’s going on.
ChatGPT disagrees that it has theory of mind. “As an AI language model, I do not have consciousness, emotions, or mental states, so I cannot have a theory of mind in the same way that a human can. My ability to predict your friend Sam's state of mind is based solely on patterns in the text data I was trained on, and any predictions I make are not the result of an understanding of Sam's mental states.”
Having studied some psychology in college, my initial reaction is that most people are going to really struggle to treat LLMs as what they are, pieces of code that are good at copying/predicting what humans would do. Instead they'll project some emotion to the responses, because there was some underlying emotions in the training data and because that's human nature. A good prediction doesn't mean good understanding, and people aren't used to needing to make that distinction.
The other day I had to assist my dad in making a zip file, later in the day he complained that his edits in a file weren't saving. After a few moments, I realized he didn't understand the read-only nature of zip files. He changed a file, saved it like usual, and expected the zipped file to update, like it everywhere else. He's brilliant as his job, after I explained that it's ready-only, he got it. LLMs and how the algorithm behind it works is hard to understand and explain to non-technical people without anthropomorphizing AI. The current controversy about AI art highlights this, I have read misunderstandings and wrong explanations even from FAANG software engineers. I am not sure if education of the underlying principles is enough, because some people will trust their own experiences over data and science.
Earlier quoted context omitted.
I wonder every time I see this take what it would mean under this definition of knowing things for a machine learning algorithm to ever know something. I find that especially important because to every appearance we are a machine learning algorithm. I don’t know how different the sort of knowing this algorithm has to the sort of knowing a human has, but you’re far more confident than I am that it’s a difference of ki…
Defining what "knowing" is would be useful, yes, and analytic philosophers in epistemology do argue about this. One attribute that's classically part of the definition of "knowing" is that the thing which is known must be true. LLMs are pretty bad at this, but perhaps that can be fixed. But I would challenge you to imagine the situation the LLM is actually in. Do you understand Thai? If so, in the following, feel fre…
As long as our minds pops out appropriate thoughts for the given context we don’t even think about the magic machinery behind the scenes that did that.
When queried about our thinking we are mostly creating a plausible story, not actually examining our own thinking.
Also, blind people can talk sensibly about many visual phenomena, having learned about them through language
I think the new LLM are giving us all so many wow’s, because “understanding” is the only kind of compression that actually works at the scale of the training data
I.e. representations are being created that reflect the actual functional, as well as associative or correlative, relations between concepts.
Earlier quoted context omitted.
Defining what "knowing" is would be useful, yes, and analytic philosophers in epistemology do argue about this. One attribute that's classically part of the definition of "knowing" is that the thing which is known must be true. LLMs are pretty bad at this, but perhaps that can be fixed. But I would challenge you to imagine the situation the LLM is actually in. Do you understand Thai? If so, in the following, feel fre…
People learn enormous amounts of things that we don’t actually “understand” in any deep way As long as our minds pops out appropriate thoughts for the given context we don’t even think about the magic machinery behind the scenes that did that. When queried about our thinking we are mostly creating a plausible story, not actually examining our own thinking. Also, blind people can talk sensibly about many visual phenom…
Earlier quoted context omitted.
If you're constructing this to rely on my prior knowledge both of the world and of English, then I must remind you that those are things the LLM does not have. We have to be careful to not allow our human inferential biases from distorting our thinking about that the models are doing.
Yeah but if you ask the model what a cat is, it'll use other words that describe a cat because they're usually used in a sentence about cats. These words must relate to cats. So if I ask you what a cat is, you'll use words that relate to cats. Sure, you may visually see these words in your head. You may visually see a cat in your head, but your output to me is just a description of a cat. That's the same thing the ne…
There's something about language generation that triggers the anthropomorphic fallacy in people. While it's impressive that GPT3 can generate language that mimics ToM-based reasoning in people, this paper doesn't get close to proving its central contention, that LLMs possess a ToM. A test that demonstrates the development of ToM in human children should not, absent compelling causal evidence and theory, be assumed to…
I think AI will ultimately force us to realize that we don't fully understand what makes us sentient - our current understanding of mind is inadequate. I do not believe that I am what thinks - rather I am what perceives myself thinking. That slight difference is extraordinarily significant. That's another debate tho.
Consciousness isn't necessarily something that may be attained - it may be possible for an AI to essentially know all things and not be actually self aware - despite even knowing what self awareness is & understanding how the concept applies to itself, with self identification, & even being able to perfectly represent an AI with self awareness - none of that is proof of sentience as all are plausible without it in a system that simply mimics with nearly perfect, or simply indistinguishable from reality, mimicry. A perfect mimic would pass all our tests and yet still is not more than a mimic. A mimic cannot exist independent of what it mimics.
I just keep wondering how long we can keep playing that we've got ourselves all figured out. All of these articles demonstrate to me that our definitions are clearly lacking if these AI are actually meeting our current understood expectations.
Obviously, an AI performance/capacity to perfectly mimic a person doesn't make that AI a person. What about a person is different from the AI that perfectly mimics a person?
I'm trying to avoid semantics - I still think this falls apart at an idea level, which means is still inherently a philosophical debate. A debate that is now possible due to the mirror that is an AI - we have a new vantage point we ought utilize.
to;dr: If an AI passes all the Turing tests today, that proves only that we need to change the test, as AI today are obviously not people yet. The standards to a new test will require us to revisit our concept of mind - conceptually, as current understanding has proven rather limited.
Earlier quoted context omitted.
Defining what "knowing" is would be useful, yes, and analytic philosophers in epistemology do argue about this. One attribute that's classically part of the definition of "knowing" is that the thing which is known must be true. LLMs are pretty bad at this, but perhaps that can be fixed. But I would challenge you to imagine the situation the LLM is actually in. Do you understand Thai? If so, in the following, feel fre…
Let me respond with an analogy of my own. Imagine you are a scientist on an alien world. The aliens primary experience the world through magnetic fields. They live deep in the atmosphere of a hot Jupiter like planet and rarely touch anything and have no eyes. Still they are intelligent beings and so quickly they are able to establish communication with you. A computer translates and you both have to become a bit more…
I think it's obviously no, because we don't have sensations of magnetic fields. It's the question of what it's like to be a bat raised by Thomas Nagel. The aliens can give us their words for conscious magnetic sensations which we can learn to use, but we won't experience them. We're basically p-zombies when it comes to non-human experiences.
> There I think the resolution is that the human following instructions does not understand Chinese but the room, the system of instructions + the human to follow them does. In a similar way obviously an individual neuron doesn't understand anything but brains do.
Searle's response to the systems objection is that we already know that brains understand Chinese. But we don't know this for the room. I would further say that brains alone don't understand anything, humans understand things as language users embedded in a social and physical world. One can invoke Wittgenstein and language games here.