|
|
|
|
|
by soloist11
722 days ago
|
|
> If your argument succeeds in proving that computer programs can't have intentionality, an essentially similar line of argument can be used to prove that human brains can't have intentionality either. I don't see why that's true. There is no formal theory for biology, the complexity exceeds our capacity for modeling it with formal language but that's not true for computers. The formal theory of computation is why it is possible to have a sequence of operations for making the parts of a computer. It wouldn't be possible to build computers if that was not the case because there would be no way to build a chip fabrication plant without a formal theory. This is not the case for brains and biology in general. There is an irreducible complexity to life and the biosphere. |
|
We don’t know to what extent that’s an inherent property of biology or whether that’s a limitation of current human knowledge. Obviously there are a still an enormous number of facts about biology which we could know but we don’t. Suppose human technological and scientific progress continues indefinitely - in principle, after many millennia (maybe even millions of years), we might get to the point where we know all we ever could know about biology. Can we be sure at that point we might not have a “formal theory” for it?
The brain is composed of neurons. Even supposing we knew everything we ever possibly could about the biology of each individual neuron, there still might be many facts about how they interact in an overall neural network which we didn’t know. Similarly, with current artificial networks, we often have a very clear understanding of how the individual computational components work - we can analyse them with those formal theories of which you are fond - but when it comes to what the model weights do, “the complexity exceeds our capacity for modeling” (if the point of the model is to actually explain how the results are produced as opposed to just reproducing them).
> There is an irreducible complexity to life and the biosphere.
We don’t know that life is irreducibly complex and we don’t know that certain aspects of computers aren’t. Model weights may well be irreducibly complex in that they are too complex for us to explain that they work and how they work even though they obviously do. Conversely, the individual computational elements in the model lack irreducible complexity, but the same is true for individual biological components - the idea that we might one day (even if centuries from now) have a complete understanding at the level of an individual neuron is not inherently implausible, but that wouldn’t mean we’d be anywhere close to a complete understanding of how a network of billions of them works in concert. The latter might indeed be inherently beyond our understanding (“irreducibly complex”) in a way in which the former isn’t