Prologue: Terrified Flashcards
Why did Hofstadter believe that computers would never reach the level of expert chess players?
Hofstadter had befriended Eliot Hearst, a chess champion and psychology professor who had written extensively on how human chess experts differ from computer chess programs. Experiments showed that expert human players rely on quick recognition of patterns on the chessboard to decide on a move rather than the extensive brute-force look-ahead search that all chess programs use. That is, these
players can quickly recognise particular configurations and strategies as instances of higher-level concepts. Hearst argued that without such a general ability to perceive patterns and recognise abstract concepts, chess programs would never reach the level of the best humans.
What changed which allowed computers to overtake humans?
in the 1980s and ’90s, computer chess saw a big jump in improvement, mostly due to the steep increase in computer speed. The best programs still played in a very unhuman way: performing extensive look-ahead to decide on the next move.
By the mid-1990s, IBM’s Deep Blue machine, with specialised hardware for playing chess, had reached the Grandmaster level, and in 1997 the program defeated the reigning world chess champion, Garry Kasparov, in a six-game match
Hofstadter had been wrong about chess, but he still stood by the other speculations
in GEB, especially the one he had listed first. What speculation was this?
QUESTION: Will a computer ever write beautiful music? SPECULATION: Yes but not soon.
Why did he speculate this about robots making music?
Music is a language of emotions, and until programs have emotions as complex as ours, there is no way a program will write anything beautiful. There can be “forgeries”—shallow imitations of the syntax of earlier music—but despite what one might think at first, there is much more to musical expression than can be captured in syntactic rules.
How was Hofstadter’s confidence in his assessment of AI was again shaken again in the 1990’s?
He encountered a program written by a musician, David Cope: Experiments in Musical Intelligence, or EMI. He had developed it to help with making music by automatically creating pieces in Cope’s specific style.
However, EMI became famous
for creating pieces in the style of classical composers such as Bach and Chopin. EMI composes by following a large set of rules, developed by Cope, that are meant to capture a general syntax of composition. These rules are applied to copious examples from a particular composer’s opus in order to produce a new piece “in the style” of that composer.
How effective was EMI?
After describing EMI, Hofstadter had asked the Eastman audience— including several music theory and composition faculty—to guess which of two pieces a pianist played for them was a (little-known) mazurka by Chopin and which had been composed by EMI. Many of the faculty, to Hofstadter’s shock, voted EMI for the first piece and “real-Chopin” for the second piece. The correct answers were the reverse.
What was Hofstadter’s reaction to EMI?
“I was terrified by EMI. Terrified. I hated it, and was extremely threatened by it. It was threatening to destroy what I most cherished about humanity. I think EMI was the most quintessential example of the fears that I have about artificial intelligence.”
What were Hofstandter’s comments at the google conference?
Hofstadter’s worries were
underlined by Google’s embrace of Ray Kurzweil and his vision of the Singularity, in which AI, empowered by its ability to improve itself and learn on its own, will quickly reach, and then exceed, human-level intelligence. Google, it seemed, was doing everything it could to accelerate that vision. While Hofstadter strongly doubted the premise of the Singularity, he admitted that Kurzweil’s predictions still disturbed him.
Hofstadter ended his talk with a direct reference to the very Google engineers in that room, all listening intently: “I find it very scary, very troubling, very sad, and I find it terrible, horrifying, bizarre, baffling, bewildering, that people are rushing ahead blindly and deliriously in creating these things.”
Hofstadter’s terror was in response to something entirely different than typical worry. It was not about AI becoming too smart, too invasive, too malicious, or even too useful. What was he fearful about?
He was terrified that intelligence, creativity, emotions, and maybe even consciousness itself would be too easy to produce—that what he valued most in humanity would end up being nothing more than a “bag of tricks,” that a superficial set of brute-force algorithms could explain the human spirit. The issue that worries him is really one of complexity. He fears that AI might show us that the human qualities we most value are disappointingly simple to mechanise.
