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Mazviita Chirimuuta

๐Ÿ‘ค Speaker
363 total appearances

Appearances Over Time

Podcast Appearances

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

It's hidden within the walls of someone else's individual subjectivity.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

As scientists, all we know are the inputs and the outputs and we'll just track those.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

And that's like a version of what you just said.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

If the inputs and the outputs, the behavior of this system are looking like what we know to be a conscious system elsewhere, well, let's just treat them as all of the same class of objects, given that the only available information is the inputs and outputs.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

I think that kind of reasoning can be fine in certain contexts, but it's a philosophical leap to say,

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

the access that we have to our own thoughts and the presence or absence of subjectivity that we're aware of with other people is irrelevant to making these decisions or judgements about what other kinds of systems can have consciousness.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

So I think it's much too quick to just go behaviorist and say, well, there's no relevant difference between X and Y.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

even if one is a person, one is a machine, just because we can say that there's some similarities in inputs and outputs.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

Yeah, so the constructivist path, which is different from the scientific realist and empiricist one, really runs with the idea that we are active makers of knowledge.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

It shouldn't be confused with the kind of constructivism that we have in some kind of more extreme branches of sociology of knowledge which say that all scientific theories are social constructs and not constrained by phenomena that have been observed in nature.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

So I'm not saying that

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

scientific theories are merely constructive in the way that like poems could be a work of imagination and so forth.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

But the idea is that there's this interactivity between humans, groups of scientists, their plans as

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

epistemic agents going out into the world with an agenda to find stuff out about certain phenomena in order to achieve certain goals, often technological, applied science goals.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

And there's some pushback from the things in nature themselves that they're investigating.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

But the idea that

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

Knowledge is always the product of this interactivity.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

So we cannot discount that there is a human framing side to this.

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

We can't go along with this idea that a scientific theory is just like reading off the source code of the universe as if

Machine Learning Street Talk (MLST)
Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

the human way of conceptualizing those phenomena had no bearing on the theory as it ultimately turns out.