Wolfram’s ‘computational irreducibility’ explains FIML perfectly

FIML is a method of inquiry that deals with the computational irreducibility of humans. It does this by isolating small incidents and asking questions about them. These small incidents are the “little pieces of computational reducibility” that Steven Wolfram remarks on at 45:34 in this video. Here is the full quote:

One of the necessary consequences of computational irreducibility is within a computationally irreducible system there will always be an infinite number of specific little pieces of computational reducibility that you can find.

45:34 in this video

This is exactly what FIML practice does again and again—it finds “specific little pieces of computational reducibility” and learns all it can about them.

In FIML practice, two humans in real-time, real-world situations agree to isolate and focus on one “specific little piece of computational reducibility” and from that gain a deeper understanding the the whole “computationally irreducible system”, which is them.

When two humans do this hundreds of times, their grasp and appreciation of the “computationally irreducible system” which is them, both together and individually, increases dramatically. This growing grasp and understanding of their shared computationally irreducible system removes most previously learned cognitive categories about their lives, or psychologies, or how they think about themselves or other humans.

By focusing on many small bits of communicative information, FIML partners improve all aspects of their human minds.

I do not believe any computer will ever be able to do FIML. Robots and brain scans may help with it but they will not be able to replace it. In the not too distant future, FIML may be the only profound thing humans will both need to and be able to do on their own without the use of AI. To understand ourselves deeply and enjoy being human, we will have to do FIML. In this sense, FIML may be our most important human answer to the AI civilization growing around us. ABN

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