@dpiponi @bjn I am not so dismissive. There was the following essay question on my qualification exam for the doctorate program in computer science #AI . “Can the economy of Bolivia feel pain?” No joke. If you couldn’t discuss this in reference to the philosophical stance of machine functional #reductionism, I think you’d probably fail. (2/3rds of my cohort failed the test as a whole).

Just saying, all late night “wrecked” discussions are not necessary just idle musing. There are some superficially odd propositions that deserve deeper thought. I will think about shoes in a new way thanks to your post.

@faz @ai_feed Thanks for posting. This is actually quite an informed essay about #AI and its place in larger discussions of science, technology and ethics. I have quibbles with details, but I agree with the author's general opinion that the human tendency to anthropomorphise almost everything within a framework of intentionality has led popular opinion of AI down an erroneous path. I also agree that systems built with AI technology are not people: They have never gone to grade school, or had a crush on a classmate, or played with a dog. Those are human experiences that machines will never have, just as we will never have machine experiences. That is not to say they are not intelligent. They are their own kind of intelligence, one which we recogize shares some common ground with our own. At the same time, it is far more different than human intelligence than is the intelligence, say, of dolphins or great apes, or whales or even an ant colony. [Plus, we get to define intelligence too. That makes it a slippery concept.]The philosophy of "machine state functionalism" gives us useful, concrete tools to analyze intelligence of whatever kind. We have learned a lot about both human and machine intelligence from functional #reductionism. What we don't understand is "awareness" and especially "awareness of self" in the way we think of our own consciousness. There are plenty of theories, but very little one can test empirically with computers. I didn't finish the essay yet, but is starts out good!

@tg9541 OK, I have read Stuart Kauffman’s book “At Home in the Universe”, and am familiar with the concept of ‘emergence’, as well as the philosophical conflict concerning #reductionism. But I am also skeptical of #math substituting for #science - as in #StringTheory.

To get to the point of this limited toot, I recall from long ago the discovery (by radiolabeling) that “biological structures are replaced every 8 weeks”, but more recent experiments refuted its generality.

@tg9541

I believe Rosen is complaining here only about one particular type of #reductionism - #computationalism.

I think he was very well aware that all anticipatory systems must maintain some (reduced) # model of reality in order to **anticipate** how things in their environments that may affect them are likely to unfold.
Science cannot dispense of "good reductionism" such as, for example, Searle's Biological Naturalism.

The excerpt is from R. L. Kuhn's "Landscape of Consciousness"

https://www.sciencedirect.com/science/article/pii/S0079610723001128#sec9

The case against #Reductionism and #Determinism built by #RobertRosen is very solid. Yet it's hard work to get workers trained in theoretical frameworks to consider it.

@ScienceCommunicator

We have 2 important considerations regarding this topic, IMO.

One is that we are not separate from the world we study. That we must always allow for interactions we find in similar subjects external to us to be operating in similar fashion inside of our own #systems. That is, we cannot build our models separately, with the outcome of purely phenomenological & physiological perspectives. Of course, where the similarities are few, those unique views are necessary. Consciousness would be one area where our experience should be included & weighed heavy in the model.

The other comes from #reductionism, and the need to incorporate boundaries, phase changes, and other #emergent phenomena that won't agree with the #linear summation during the reconstruction of the parts we identified on the way down.

So going down the chain of molecules, elements, and atoms, for example, is not different from examining #evolution connections, or life itself. There is no reverse at some points, and even where there is time reversal #symmetry, the paths are not always direct, 1:1 increments. (see 'islands of stability', for example)

We have a bad tendency of always ending up framing it in black or white terms, like " #nature vs nurture", when the actual situations nearly always require both.

One of the unfortunate elements of the #scientific method centered on reduction is that the first impression (indeed very strong) comes in the results section, from the questions asked at the start. Those have been stripped of all #context variation & complexity, and that is where it leaves off in most cases. For the vast majority of humans, the deeper layers are never seen or explored; the simplified meme is what propagates most prolifically.

Our mission, should we choose to accept it, is to layer the #complexity back in, one layer at a time, and continue our pursuit of higher #knowledge. This will require some modifications to our current system!