Book review: Beyond Boundaries: The New Neuroscience of Connecting Brains with Machines and How It Will Change Our Lives, by Miguel Nicolelis.
This book presents some ambitious visions of how our lives will be changed by brain-machine and brain to brain (“mind meld”) interfaces, along with some good reasons to hope that we will adapt well to them and think of machines and other people as if they are parts of our body. Many people will have trouble accepting his broad notion of personal identity, but I doubt they will find good arguments against it.
But I wish I’d skipped most of the first half, which focuses on the history of neuroscience research, with too much attention to debates over the extent to which brain functions are decentralized.
He’s disappointingly vague about the obstacles that researchers face. He hints at problems with how safe and durable an interface can be, but doesn’t tell us how serious they are, whether progress is being made on them, etc. I also wanted more specific data about how much information could be communicated each way, how precisely robotic positioning can be controlled, and how much of a trend there is toward improving those.
Book Review: The Singularity Is Near : When Humans Transcend Biology by Ray Kurzweil
Kurzweil does a good job of arguing that extrapolating trends such as Moore’s Law works better than most alternative forecasting methods, and he does a good job of describing the implications of those trends. But he is a bit long-winded, and tries to hedge his methodology by pointing to specific research results which he seems to think buttress his conclusions. He neither convinces me that he is good at distinguishing hype from value when analyzing current projects, nor that doing so would help with the longer-term forecasting that constitutes the important aspect of the book.
Given the title, I was slightly surprised that he predicts that AIs will become powerful slightly more gradually than I recall him suggesting previously (which is a good deal more gradual than most Singulitarians). He offsets this by predicting more dramatic changes in the 22nd century than I imagined could be extrapolated from existing trends.
His discussion of the practical importance of reversible computing is clearer than anything else I’ve read on this subject.
When he gets specific, large parts of what he says seem almost right, but there are quite a few details that are misleading enough that I want to quibble with them.
For instance (on page 244, talking about the world circa 2030): “The bulk of the additional energy needed is likely to come from new nanoscale solar, wind, and geothermal technologies.” Yet he says little to justify this, and most of what I know suggests that wind and geothermal have little hope of satisfying more than 1 or 2 percent of new energy demand.
His reference on page 55 to “the devastating effect that illegal file sharing has had on the music-recording industry” seems to say something undesirable about his perspective.
His comments on economists thoughts about deflation are confused and irrelevant.
On page 92 he says “Is the problem that we are not running the evolutionary algorithms long enough? … This won’t work, however, because conventional genetic algorithms reach an asymptote in their level of performance, so running them for a longer period of time won’t help.” If “conventional” excludes genetic programming, then maybe his claim is plausible. But genetic programming originator John Koza claims his results keep improving when he uses more computing power.
His description of nanotech progress seems naive. (page 228) “Drexler’s dissertation … laid out the foundation and provided the road map still being followed today.” (page 234): “each aspect of Drexler’s conceptual designs has been validated”. I’ve been following this area pretty carefully, and I’m aware of some computer simulations which do a tiny fraction of what is needed, but if any lab research is being done that could be considered to follow Drexler’s road map, it’s a well kept secret. Kurzweil then offsets his lack of documentation for those claims by going overboard about documenting his accurate claim that “no serious flaw in Drexler’s nanoassembler concept has been described”.
Kurzweil argues that self-replicating nanobots will sometimes be desirable. I find this poorly thought out. His reasons for wanting them could be satisfied by nanobots that replicate under the control of a responsible AI.
I’m bothered by his complacent attitude toward the risks of AI. He sometimes hints that he is concerned, but his suggestions for dealing with the risks don’t indicate that he has given much thought to the subject. He has a footnote that mentions Yudkowsky’s Guidelines on Friendly AI. The context could lead readers to think they are comparable to the Foresight Guidelines on Molecular Nanotechnology. Alas, Yudkowsky’s guidelines depend on concepts which are hard enough to understand that few researchers are likely to comprehend them, and the few who have tried disagree about their importance.
Kurzweil’s thoughts on the risks that the simulation we may live in will be turned off are somewhat interesting, but less thoughtful than Robin Hanson’s essay on How To Live In A Simulation.
A couple of nice quotes from the book:
(page 210): “It’s mostly in your genes” is only true if you take the usual passive attitude toward health and aging.
(page 301): Sex has largely been separated from its biological function. … So why don’t we provide the same for … another activity that also provides both social intimacy and sensual pleasure – namely, eating?