Status Updates From Re-Engineering Philosophy f...

Really enjoying this!

I was hoping I could understand this like I've learned to understand Stuart Kauffman (which is ongoing). Here we have difficult matter; perhaps beyond my capacity, and curiosity in which I think there must be something really interesting stuff in this book.

A prioristic views of method are incompatible with the values of science. Investigations should be performed in the real world, not in the idealized conceptual worlds of our own construction. Models that limit an agent to too few degrees of freedom are often misleading. Logically necessary consequences from such models are irrelevant. Models that hold in principle but not in practice should not hold our attention.

Overly strict normative idealizations are compromising to human rationality & scientific practice. Reasonable goal setting has been shown to result in better performance. Yet our implicit models are more demanding than plausible. Idealizing human rationality ignores the constraints of our biology. What we really do is make mistakes & learn by studying how things break down. Why not develop our heuristics around this?

The dominant reductionist science is flawed by idealizations about rational decision which requires unrealistic degrees of knowledge and inferencial power. In reality we craft heuristic tools that are neither axiomatic nor algorithmic in origin but refined with experience. Rather than formalisms and foundations, science should rely on contextual adaptability that is tolerant of and engineered to learn from error.