this post was submitted on 15 May 2024
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I have many conversations with people about Large Language Models like ChatGPT and Copilot. The idea that "it makes convincing sentences, but it doesn't know what it's talking about" is a difficult concept to convey or wrap your head around. Because the sentences are so convincing.

Any good examples on how to explain this in simple terms?

Edit:some good answers already! I find especially that the emotional barrier is difficult to break. If an AI says something malicious, our brain immediatly jumps to "it has intent". How can we explain this away?

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[–] [email protected] 7 points 6 months ago* (last edited 6 months ago) (1 children)

After reading some of the comments and pondering this question myself, I think I may have thought of a good analogy that atleast helps me (even though I know fairly well how LLM's work)

An LLM is like a car on the road. It can follow all the rules, like breaking in front of a red light, turning, signaling etc. However, a car has NO understanding of any of the traffic rules it follows.

A car can even break those rules, even if its behaviour is intended (if you push the gas pedal at a red light, the car is not in the wrong because it doesn't KNOW the rules, it just acts on it).

Why this works for me is that when I give examples of human behaviour or animal behaviour, I automatically ascribe some sort of consciousness. An LLM has no conscious (as far as I know for now). This idea is exactly what I want to convey. If I think of a car and rules, it is obvious to me that a car has no concept of rules, but still is part of those rules somehow.

[–] [email protected] 3 points 6 months ago* (last edited 6 months ago) (1 children)

Thing is a conscience (and any emotions, and feelings in general) is just chemicals affecting electrical signals in the brain... If a ML model such as an LLM uses parameters to affect electrical signals through its nodes then is it on us to say it can't have a conscience, or feel happy or sad, or even pain?

Sure the inputs and outputs are different, but when you have "real" inputs it's possible that the training data for "weather = rain" is more downbeat than "weather = sun" so is it reasonable to say that the model gets depressed when it's raining?

The weightings will change leading to a a change in the electrical signals, which emulates pretty closely what happens in our heads

[–] [email protected] 4 points 6 months ago* (last edited 6 months ago) (1 children)

Doesn't that depend on your view of consciousness and if you hold the view of naturalism?

I thought science is starting to find more and more that a 100% naturalistic worldview is hard to keep up. (E: I'm no expert on this topic and the information and podcast I listen to are probably very biased towards my own view on this. The point I'm making is that to say "we are just neurons" is more a disputed topic for debate than actual fact when you dive a little bit into neuroscience)

I guess my initial question is almost more philosophical in nature and less deterministic.

[–] [email protected] 2 points 6 months ago (1 children)

I'm not positive I'm understanding your term naturalistic but no neuroscientist would say "we are just neurons". Similarly no neuroscientist would deny that neurons are a fundamental part of consciousness and thought.

You have plenty of complex chemical processes interacting with your brain constantly - the neurons there aren't all of who you are.

But without the neurons there: you aren't anyone anymore. You cease to live. Destroying some of those neurons will change you fundamentally.

There's no disputing this.

[–] [email protected] 1 points 6 months ago

I agree with you, and you worded what I was clumsily trying to say. Thank you:)

With naturalism I mean the philosphical idea that only natural laws and forces are present in this world. Or as an extension, the idea that here is only matter.