The book’s premise is that in about a century, it will be possible to scan human brains at "fine enough spatial and chemical resolution," and to combine that with good-enough models of signal-processing functions of brain cells, "to create a cell-by-cell dynamically executable model of the full brain in artificial hardware, a model whose signal input-output behavior is usefully close to that of the original brain."
Like Bostrom and Kurzweil I think this guy is seriously underestimating the difficulty of biology. I don't believe in souls or non-computable woo going on in our brains. I do believe that biology is insanely complicated compared to computing or physics; physicists, engineers, and people from a computing background who've never worked in biology tend to handwave incredibly difficult problems. See also: the long and mostly-unsuccessful history of people who thought that they could replace animal/cell culture drug testing with models in silico.
On top of the sheer audacious difficulty of creating whole brain emulations, there's the problem of competing with boring old "narrow" AI. Surely an economist of all people should recognize the feedback loop that makes narrow AI profitable first, which attracts more investment, which unlocks more capabilities without biological emulation... how many of today's jobs are going to be left un-done by narrow AI a century from now, even if whole brain emulations are finally practical then?
Like Bostrom and Kurzweil I think this guy is seriously underestimating the difficulty of biology. I don't believe in souls or non-computable woo going on in our brains. I do believe that biology is insanely complicated compared to computing or physics; physicists, engineers, and people from a computing background who've never worked in biology tend to handwave incredibly difficult problems. See also: the long and mostly-unsuccessful history of people who thought that they could replace animal/cell culture drug testing with models in silico.
On top of the sheer audacious difficulty of creating whole brain emulations, there's the problem of competing with boring old "narrow" AI. Surely an economist of all people should recognize the feedback loop that makes narrow AI profitable first, which attracts more investment, which unlocks more capabilities without biological emulation... how many of today's jobs are going to be left un-done by narrow AI a century from now, even if whole brain emulations are finally practical then?