Gödel, Escher, Bach: An Eternal Golden Braid
by Douglas R. Hofstadter (1979)
2022 reads, 19/20:
“This is axiom”
The above quote is not from this book, but instead, the final lyric in the final song off Bon Iver’s 2011 album, Bon Iver, Bon Iver. These three words encapsulate everything that Justin Vernon was trying to say not only in that whole song, but the whole album: we are here, and in this place, we are self-evident. In math, an axiom is the strongest statement you can make, something that cannot be proved because of its self-evidence (for example the first equality axiom, which states $x = x$, i.e. a number equals itself). And much like I am comparing this foundational mathematical term to music, Hofstadter does the same in his book Gödel, Escher, and Bach: An Eternal Golden Braid.
Hofstadter masterfully weaves Gödel’s Incompleteness Theorem, Bach’s fugues, and Escher’s drawings together to create a map between the neurological structure of the brain and the rise of artificial intelligence. His starting point is defining a ‘strange loop,’ a type of self-reference which leads you back to the original statement, and works from there. If you hold on for the whole ride, his final chapters provide an interesting and original take on minds and machines. In between these chapters lie dialogues between a slew of characters such as the tortoise and Achilles, which are not just entertaining, but also excellent at priming you for the ideas about to be introduced in the next chapter. Some did not enjoy the dialogues, but I thought they were some of the best parts of the book.
At times, this does read like a textbook, but it’s not dry or boring at all; Hofstadter is inviting us to try to get to the point before he gets there, which makes reading GEB almost conversational. I started to lose a bit of interest in the latter half of the Part II, solely because I am not super interested in genetics; to me, Hofstadter is at his best when he is writing about logic, paradoxes, and writing dialogues with hidden meanings. Others would disagree, however, as some really enjoy the neurological aspects, and don’t see the point of the math. And as I mentioned, you don’t really get to the crux of what Hofstadter wants to convey in this book until the final three chapters, which could turn off some people.
Anyone who has an interest in math, puzzles, computer science, neurology, genetics, or even art would at least moderately be interested in what Hofstadter is saying. By no means is a formal background in math required, you just need interest. The reason it took me so long to finish this was not because it was boring, in fact the opposite – his ideas need time to marinate before you go on. In this book, the journey was much better than the destination.