It was an absolutely, amazingly brilliant work from a totally unknown first-time professor/author.
So much so that Scientific American’s Martin Gardner praised it to the skies, rightly so, pushing it to the best-seller book lists, and not because was yet another detective novel or a political rant or a ghostwritten memoir by someone rich and famous.
No, it was an well-written, highly entertaining book about the connections among mathematics, computer languages, English and other ancient and modern human languages, DNA code, artificial intelligence, science, history, music, what it means to be human and to think and do stuff. Brilliant, original ideas and clear, sparkling language on every beautifully-written page — with lots of illustrations and diagrams, too!!
The fact that the author’s father (Robert) shared the Nobel Prize in nuclear Physics in 1961 considerably upped the odds that Hofstadter would grow up in intellectual atmosphere that valued independent thinking rather than mindless obedience. According to this Atlantic review, his parents more than tolerated young Douglas’ tendency to go off on various tangents and delve into them deeply and thoroughly and even obsessively for some period of time, until he felt he had another hunch or tangent, which he would again jump into with both feet and all his weight. And all of it carefully and brilliantly documented.
Those documents, I discovered in reading this essay, became the book GEB.
He and the rest of the Artificial Intelligence community agree that they have gone in different directions since then.
AI today no longer tries to imitate the actions of the human brain, but they are doing some pretty amazing stuff with sheer computational speed and power.
Hofstadter thinks that may all be very nice, but that approach does not really help understand how humans think — how we make all those connections in our head in which we strip off 99% of the details about one thing and find one or two ways in which it relates to another thing, constantly and unexpectedly
[I gave some copies to some of my students; I wish I could have afforded to give away more. Instead, I developed lists of books on math and science and math field trips and tessellations and had kids read some of the books and do various projects that I though would illustrate some topic and develop pride and character and a belief that math of whatever sort I was teaching to them was actually worth something and useful in real life as well as pretty cool as an abstract creation of humanity...]
Douglas Hofsadter, the author of GEB is not working for Google or Apple or any other such company helping to develop complex computer programs that do complex things either very well at least some of the time — because DH thinks they won’t lead to more understanding of human or animal intelligence. According to this review, DH has the greatest job in the world — he doesn’t have to teach classes. or attend any meetings at all, or perform experiments. or write grant applications. For a number of years,. he took over the Mathematical Games that Martin Gardner used to write for SciAm, and renamed it “Metamagical Themas” – an anagram of the original name.
A few interesting quotes from the article: (The man who would teach machines to think…)
“Correct speech isn’t very interesting; it’s like a well-executed magic trick—effective because it obscures how it works. What Hofstadter is looking for is “a tip of the rabbit’s ear … a hint of a trap door.”
N ow, some quotes from Hofstadter himself, which I got from a collection of his quotes, and which remind me why I thopught his work was so brilliant in the first place:
Meaning lies as much
in the mind of the reader
as in the Haiku.
“How gullible are you? Is your gullibility located in some “gullibility center” in your brain? Could a neurosurgeon reach in and perform some delicate operation to lower your gullibility, otherwise leaving you alone? If you believe this, you are pretty gullible, and should perhaps consider such an operation.”
“Hofstadter’s Law: It always takes longer than you expect, even when you take into account Hofstadter’s Law”
“Sometimes it seems as though each new step towards AI, rather than producing something which everyone agrees is real intelligence, merely reveals what real intelligence is not. ”
“In the end, we self-perceiving, self-inventing, locked-in mirages are little miracles of self-reference.”
“I would like to understand things better, but I don’t want to understand them perfectly.”
“This idea that there is generality in the specific is of far-reaching importance.”