Review: The AI Delusion
My rating: 4 of 5 stars
A.I. is the modern snake oil solution to all your work needs and it's likely to screw things up. Or at least, that's Smith's general argument as he breaks down the fundamental problems with artificial intelligence. One such problem is the fact that even labeling it "intelligence" tricks people into a false sense of security about what AI does. A.I. does not have intelligence or intention and therefore, its ability to do the things that so many people claim it can do is disconcerting and misleading. Essentially, Smith argues that most of AI works akin the Texas Sharp-Shooter sham wherein either a gunslinger shoots a bunch of holes into a wall and then puts the target over one of the shots and say "look, I got a bullseye" or points and shoots at a bullseye and misses, but then moves the target over. Because computers just crunch numbers without any sense of relation or meaning, the end result is that it evitably finds connections. Essentially, all that big data does is torture the data until it confesses with some kind of relationship. The problem as Smith highlights here is that if you put together enough data and mix it up enough, it will create patterns but some of that pattern is the nature of randomization (that is, part of the randomness of randomness is to occasionally have patterns). He demonstrates this consistently throughout by reminding that correlation is not causation but that also the correlation is often spurious at best and A.I. does not have intelligence enough to know what is evidently spurious and what isn't. What I like about Smith's book is the critical way he breaks down A.I. and makes its underpinnings a bit more comprehensive. Now, this isn't consistent throughout the book and there are places where I get lost and am just along for the ride. But much of his work is consistently accessible. It also helps that he uses lots of examples to demonstrate his points and shows time and again, how patterns even in meaningless data could be found to be correlative (he routinely shares statistical relationships among different things, only to reveal that he made up the initial numbers and the computer "found" the relationship). However, I think I also get a bit concerned that his argument seems to largely say that all research is bunk or that we should trust any research. On the one hand, I get that, but on the other, it means that we all need to become specialists in everything that we might need to rely on and that just doesn't seem feasible either. Finally, I wish he would have better discussed or addressed the idea that if his argument is true, then how does he explain the places where it at least appears that A.I. is getting things right. Regardless, it's a useful book to consider for anyone who might be encountering AI in their realm and see people blindly accepting it.
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