Tuesday, March 31, 2015

Review: How to Create a Mind by Ray Kurzweil

Hello again! Finally I can get back to business now that the Spring musical is over and most of the teachers have recovered from their post-break assignment panic. I read this book a few weeks ago, over my Spring break. It was an interesting book, though very different from Barrat's pessimistic analysis of the state of AI research.

In How to Create a Mind, Kurzweil focuses on trying to predict AI's next step through a mix of neuroscience, mathematical analysis, and philosophy. I picked this book over some of Kurzweil's more famous works, like The Singularity is Near, because I wanted something a little more technical than I assumed those books would be, and I wasn't disappointed.
But the great things about the book are: a) it's easy to read, and b.) fairly well cited. I've seen lots of criticism online about Kurzweil "dumbing down" the theories he talks about in the book, which range from discussions of Hidden Markov Models and the Pattern Recognition Theory of Mind,  to thought experiments like the Chinese Room. I think these critics miss the point of the book - it's not meant to be a textbook. It's meant for the masses, the people looking to understand more about AI and how it works, and in that respect it works very well.

I do have some doubts about Kurzweil's qualifications as a neuroscientist. (Not that I'm any more qualified.) He spends a good portion of the book talking about his Pattern Recognition Theory of Mind (PRTM), where he theorizes that the neocortex of the brain is made up of multi-neuron "pattern-recognizers" that are arranged hierarchally to allow for the recognition of more and more complex patters. Kurzweil does a LOT of guessing in these chapters, from the number of neurons in each pattern recognizers to how they would be structured in the brain, that he almost stipulates as fact. His explanation of the theory is convincing, at least to someone like me; Plus the inspiration has created several useful AI tools, such as the Hidden Markov Model and Hidden Temporal Model. But I'd have to do more of my own research to say anything substantial about the validity of the theory.
Kurzweil's thoughts on consciousness and the mind, the focus of the second half of the book, match up pretty well with my own, and I enjoyed reading his justifications for them. They make for good argument fodder, and, as I'm sure you know, argue I do. And more than anything else, this second half is a place of argument: Kurzweil goes out of his way to defend his predictions and disprove his detractors and their positions. In some cases it seems almost a little desperate, and one chapter late in the book becomes quite tedious as Kurzweil tries to defend his Singulatarian movement (On which my views haven't changed. See my review of Barrat's Our Final Invention).

But you shouldn't let this criticism stop you from checking out the book. It tends toward overstatement and futuristic optimism, but, so does Kurzweil. The information is well cited, inspiring, interesting, and a great base for further research. I would wholeheartedly recommend the book to anyone interested in AI - So long as they know nothing there, or anywhere else, is the final word.