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Monday, December 02, 2019

Review: The Big Picture

The Big Picture is Sean Carroll's philosophy book. I wasn't sure what to expect when I was reading it, and the early part reminded me of his Great Courses series  on Time. But once past that, he goes into ontology, ethics, and as well as that philosophical question: "What is Real?" The unique part of this, of course, is that Caroll is a physicist, so we get a unique view on what Quantum Mechanics means in terms of What is Real.

I especially loved the section on ESP and Telekinesis, having never heard someone explain it quite this way: in particular, since we've pretty much uncovered all the forces that can affect us (both on the microscopic or macroscopic level), there's very little chance that there's another force that can affect the world, so ESP/Telekinesis advocates have literally nothing to work with. (This also applies to stuff like force fields and other science fiction apparatus)

There's a great section about Bayesian statistical thinking, and how to evaluate priors and how to apply that to theories, but again, Carroll takes a twist and applies it to "how should you think about the existence of God?" This is all done with a scientist's enjoyment of exploratory thinking, and interjected with a personal memoir that I enjoyed reading.
Here in the early years of the twenty-first century, a majority of philosophers and scientists are naturalists. But in the public sphere, at least in the United States, on questions of morality and meaning, religion and spirituality are given a preeminent place. Our values have not yet caught up to our best ontology. They had better start catching up. When it comes to deciding how to live, we’re like that first fish flapping up onto land: faced with a new world of challenges and opportunities, and not yet really adapted to it. (KIndle Loc 6351)
I really had enjoyed this book. Sure, there's lots of stuff in here that you've probably read about before, but the unique twists that Caroll brings to that material, be it quantum mechanics or Bayesian statistical thinking are worth the time. Recommended.

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