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By: George Towner
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Thinking Like a Computer is based on an intriguing new proposition: that computer designers, who are charged to make machines think like people, have come up with ideas about human knowledge that traditional science missed. The author, George Towner, was trained in philosophy and then spent 30 years working as an Apple engineer. His book tries to imagine what a computer might say if it were asked how it understands our world. Towner’s findings question several scientific traditions. While computers can do the math, for example, they treat it as just another language. A computer’s heart (so to speak) is not in numbers, it’s in set theory. The primary way machines understand our world is through analog-to-digital (A-to-D) conversion, which sees the world as sets of bits. Because there are many ways to do A-to-D conversions, computer designs are not based on finding ultimate knowledge—they only try for more efficient understanding. Even space and time, in Towner’s analysis, are just useful A-to-D algorithms adopted by living things on our planet. Towner’s book explains all this in crystal-clear prose, with a minimum of jargon. Every train of ideas is accessible to the average reader, even those that result in offbeat conclusions. As a kind of proof of concept, Towner devotes the last two chapters of Thinking Like a Computer to psychology and sociology. These are areas of knowledge that tend to baffle traditional science but they fit right into what Towner calls “Digital Reality theory.” For example, political arguments—so intractable to scientific reasoning—show up as simple lifestyle choices when you analyze them by thinking like a computer. Whatever the reader’s opinions, Towner remains neutral. He sets his book’s goal at the beginning of the first chapter: “It assembles a coherent and believable mental picture out of principles that have traditionally been scattered among various scholarly disciplines. Whether that picture is true to life is a matter of judgment in which you are the judge,”
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