I don't think they're speaking too strongly. I think a lot of the time when we correctly infer causality without empirically interacting with the system, it's because we have built up significant categorical experience about more atomic systems we were able to interact with.

In my view, a lot of things that are noninteractively inferred are compositions of more fundamental things that required empirical experience. When you've had the causality of gravity thoroughly beaten into you at a young age, a lot of other things seem intuitive that would otherwise completely fall outside a framework for being unempirically learned.

Do you have a specific counterexample of causality you can infer without interaction or empirical experience of something related?

Caveats: I'm not a neurologist or psychologist, so this is mostly philosophical speculation on my part.

We think we're so smart because we causally understand the world, but it took us a very long time to collectively discover these principles. A human alone would not be so smart.

I think this confuses (fact) knowledge and the ability to recognize causal relations.

A human can never be smarter than said human: Our brains are not connected and we can't share capacity with others.

So, discovering causality is always an individual experience. And that happens likely by "playing" with "the world".

I think it's noticeable that smarter animals are more playful. Which is also a hint that points to the fundamental importance of interaction with the world as a prerequisite for "smartness". Additionally the capabilities of the "sensors" and "actors" that make interaction with the world possible in the first place seem to be crucial to develop "smart behavior".

The part about the "sensors" seems quite obvious. I think one can gain a better general understanding of some thing if one can "experience" it in more than one "dimension".

And the "actors" allow one to perform "experiments" with the things around one, and find out this way how that thing "works" or is supposed to be "used".

That's actually the behavior that can be observed in children of all kinds of "smarter" species. So it seems to be at least linked somehow to "smartness".

Empirical evidence is a special case observation. If you observe the whole universe in its entirety, you could separate moments that effectively followed whatever conditions you might set in a lab. You can't act on the system, but you can forever tune your models to match the infinite observations you could record. At that point the separation between observation derived knowledge versus experiential knowledge is meaningless (it's just hard to imagine a universal model manifesting without having used experiental knowledge along the way).

Whether you swing the bat or just watch it hit the ball into the sky, you have the prerequisites needed to reason about the interaction.

A more entertaining question is how a system comes to believe causality (i.e. comes to believe that things can and must have causes)

I agree. To say we're able to influence the system is to assume free will, which I believe is an undecidable problem. Ultimately this is just a matter of semantics, which makes this thread rather pointless.

It does not need to assume free will, which indeed is a much harder philosophical issue - it needs to assume that the decisions of the intervention are caused by factors outside of the system you're studying (which usually isn't the whole world), which is easy to get if you have some actual external influence, and very hard to determine if you're purely observing.

For example, if you're allocating patients in control and treatment group based on a roll of dice - the dice don't have free will, but they are influencing the "system" of the patients and their treatment, while that system is not causually influencing the dice rolls.

For another example, if a baby is "experimenting" by babbling (a key part of language acquisition, https://en.wikipedia.org/wiki/Babbling), it's not necessary or relevant to decide whether free will is involved, the baby obtains useful experimental results of what sound experiences are caused by which attempts to move the tongue/mouth/etc, even if there's no free will and the attempts to move the tongue/mouth/etc are also deterministically caused by the sensory experiences of the baby.

> (it's just hard to imagine a universal model manifesting without having used experiental knowledge along the way)

That's actually the point!

I think we have a hard time disconnecting our personal experience with the observations we make. When we look at a photograph of a person riding a bicycle down a path, even if we've never ridden a bicycle we've likely been outdoors, stood on a path, felt wind when we moved, etc. We may not be able to accurately simulate the experience in our mind but we can get close.

On the other hand, the starting point for an ML system interpreting that same image is essentially a stream of scalar values that tend to demonstrate multiple layers of periodicity (3-4 byte intervals for RGBA and then another layer per line of rasterized image data and yet another per frame if it's a video).

Here's a quick experiment. Let the video linked below play for a five count (sound is essential but a bit intense so maybe moderate the volume first) so you have some confidence it's not just me playing a rude trick, then close your eyes for a five count. There's going to be a major change in the sound when you get near 'five', now try to imagine how the scene changed before opening your eyes again:

https://youtu.be/qnL40CbuodU?t=25

I think without any reference from an embodied perspective, we're asking ML systems to understand the sounds (which are also streams of scalar values that demonstrate periodicity) the same way we interpret the representation visually.

(Also if you enjoyed the example above check out these two channels, some of them are mindblowing)

https://www.youtube.com/user/jerobeamfenderson1

https://www.youtube.com/c/ChrisAllenMusic

And a fun video explaining it all - https://www.youtube.com/watch?v=4gibcRfp4zA

An interesting related idea is inverse reinforcement learning. We watch how other people interact with a system to estimate a reward function and then we later test it out ourselves. Either directly with an environment or inside our own mental model of the environment. Simply "observing the world" can give us data about how to learn in an environment we've never interacted with before; only by watching others interact with it.

That's true. But the key seems to remain the "interaction with the world".

Maybe it's semantics but interacting with a simulation of the world is actually more important. In a pure sense, this doesn't require any actual real world interaction. This concept is usually referred to offline and off-policy reinforcement learning.

If you're saying that interaction in any sense is important, I'd very much agree that unsupervised learning and supervised learning aren't equipped to handle reinforcement learning problems. Correct framing of a problem is necessary to achieve a desired property like causality.

> We most certainly can

That is a very, very strong statement that requires some proof to go with such a strong statement of certainty.

While we can learn that the ball's change of movement just fine without swinging the bat, we can only do that because we are generalizing from a large body of knowledge that we devoloped by experimenting on the world using our body.

I am not aware of a single piece of evidence that an agent can use purely observational learning to ever aquire the causal knowledge of the real world to sufficient level to make those sorts of inferences with any sort of reasonable accuracy.

I'd link studies about children aping things they have only seen through a window, but I suspect you'll quickly argue out of the bounds of those studies and so I won't.

Right. "World" includes us. When we perform actions we observe ourselves doing them and then we observe the consequences.

That is the only way we can learn anything, by observing. And what else is there to observe than the "world"? We can observe our own thinking process but that is part of the world too. I would say. It is definitely not "out of this world" :-)

yes, we learn causal reasoning by observing consequences, we can't learn by simply watching without acting

After interacting with the world, we can learn from passive observation. No human has ever learned anything about causation without first spending a while experimenting in the world.