[discussion of Hofstadter2023] Prologue: Terrified …The [Google/Hofstadter] meeting, in May 2014, had been organized by Blaise Agüera y Arcas, a young computer scientist who had recently left a top position at Microsoft to help lead Google’s machine intelligence effort…The meeting was happening so that a group of select Google AI researchers could hear from and converse with Douglas Hofstadter, a legend in AI and the author of a famous book cryptically titled Gödel, Escher, Bach: an Eternal Golden Braid, or more succinctly, GEB (pronounced “gee-ee-bee”). If you’re a computer scientist, or a computer enthusiast, it’s likely you’ve heard of it, or read it, or tried to read it…Chess and the First Seed of Doubt: The group in the hard-to-locate conference room consisted of about 20 Google engineers (plus Douglas Hofstadter and myself), all of whom were members of various Google AI teams. The meeting started with the usual going around the room and having people introduce themselves. Several noted that their own careers in AI had been spurred by reading GEB at a young age. They were all excited and curious to hear what the legendary Hofstadter would say about AI.

Then Hofstadter got up to speak. “I have some remarks about AI research in general, and here at Google in particular.” His voice became passionate. “I am terrified. Terrified.”

Hofstadter went on. [In the following sections, quotations from Douglas Hofstadter are from a follow-up interview I did with him after the Google meeting; the quotations accurately capture the content and tone of his remarks to the Google group.] He described how, when he first started working on AI in the 1970s, it was an exciting prospect but seemed so far from being realized that there was no “danger on the horizon, no sense of it actually happening.” Creating machines with human-like intelligence was a profound intellectual adventure, a long-term research project whose fruition, it had been said, lay at least “one hundred Nobel prizes away.” Hofstadter believed AI was possible in principle: “The ‘enemy’ were people like John Searle, Hubert Dreyfus, and other skeptics, who were saying it was impossible. They did not understand that a brain is a hunk of matter that obeys physical law and the computer can simulate anything … the level of neurons, neurotransmitters, et cetera. In theory, it can be done.” Indeed, Hofstadter’s ideas about simulating intelligence at various levels—from neurons to consciousness—were discussed at length in GEB and had been the focus of his own research for decades. But in practice, until recently, it seemed to Hofstadter that general “human-level” AI had no chance of occurring in his (or even his children’s) lifetime, so he didn’t worry much about it.

Near the end of GEB, Hofstadter had listed “10 Questions and Speculations” about artificial intelligence. Here’s one of them: “Will there be chess programs that can beat anyone?” Hofstadter’s speculation was “no.” “There may be programs which can beat anyone at chess, but they will not be exclusively chess players. They will be programs of general intelligence.”⁴

At the Google meeting in 2014, Hofstadter admitted that he had been “dead wrong.” The rapid improvement in chess programs in the 1980s & 1990s had sown the first seed of doubt in his appraisal of AI’s short-term prospects. Although the AI pioneer Herbert Simon had predicted in 1957 that a chess program would be world champion “within 10 years”, by the mid-1970s, when Hofstadter was writing GEB, the best computer chess programs played only at the level of a good (but not great) amateur. 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. During a game, the best human players can perceive a configuration of pieces as a particular “kind of position” that requires a certain “kind of strategy.” That is, these players can quickly recognize particular configurations and strategies as instances of higher-level concepts. Hearst argued that without such a general ability to perceive patterns and recognize abstract concepts, chess programs would never reach the level of the best humans. Hofstadter was persuaded by Hearst’s arguments.

However, 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 specialized hardware for playing chess, had reached the Grandmaster level, and in 1997 the program defeated the reigning world chess champion, Garry Kasparov, in a 6-game match. Chess mastery, once seen as a pinnacle of human intelligence, had succumbed to a brute-force approach.

Music: The Bastion of Humanity… Hofstadter had been wrong about chess, but he still stood by the other speculations in GEB…Hofstadter described this speculation as “one of the most important parts of GEB—I would have staked my life on it.”

Hofstadter then recounted a lecture he gave at the prestigious Eastman School of Music, in Rochester, New York. 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. As one audience member described later, “The first mazurka had grace and charm, but not ‘true-Chopin’ degrees of invention and large-scale fluidity … The second was clearly the genuine Chopin, with a lyrical melody; large-scale, graceful chromatic modulations; and a natural, balanced form.” Many of the faculty agreed and, to Hofstadter’s shock, voted EMI for the first piece and “real-Chopin” for the second piece. The correct answers were the reverse.

In the Google conference room, Hofstadter paused, peering into our faces. No one said a word. At last he went on. “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.”

Google and the Singularity: Hofstadter then spoke of his deep ambivalence about what Google itself was trying to accomplish in AI—self-driving cars, speech recognition, natural-language understanding, translation between languages, computer-generated art, music composition, and more. 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. “I was terrified by the scenarios. Very skeptical, but at the same time, I thought, maybe their timescale is off, but maybe they’re right. We’ll be completely caught off guard. We’ll think nothing is happening and all of a sudden, before we know it, computers will be smarter than us.” If this actually happens, “we will be superseded. We will be relics. We will be left in the dust. Maybe this is going to happen, but I don’t want it to happen soon. I don’t want my children to be left in the dust.”

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.”

Why Is Hofstadter Terrified? I looked around the room. The audience appeared mystified, embarrassed even. To these Google AI researchers, none of this was the least bit terrifying. In fact, it was old news…Hofstadter’s terror was in response to something entirely different. It was not about AI becoming too smart, too invasive, too malicious, or even too useful. Instead, 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.

As GEB made abundantly clear, Hofstadter firmly believes that the mind and all its characteristics emerge wholly from the physical substrate of the brain and the rest of the body, along with the body’s interaction with the physical world. There is nothing immaterial or incorporeal lurking there. 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 mechanize. As Hofstadter explained to me after the meeting, here referring to Chopin, Bach, and other paragons of humanity, “If such minds of infinite subtlety and complexity and emotional depth could be trivialized by a small chip, it would destroy my sense of what humanity is about.”

…Several of the Google researchers predicted that general human-level AI would likely emerge within the next 30 years, in large part due to Google’s own advances on the brain-inspired method of “deep learning.”

I left the meeting scratching my head in confusion. I knew that Hofstadter had been troubled by some of Kurzweil’s Singularity writings, but I had never before appreciated the degree of his emotion and anxiety. I also had known that Google was pushing hard on AI research, but I was startled by the optimism several people there expressed about how soon AI would reach a general “human” level. My own view had been that AI had progressed a lot in some narrow areas but was still nowhere close to having the broad, general intelligence of humans, and it would not get there in a century, let alone 30 years. And I had thought that people who believed otherwise were vastly underestimating the complexity of human intelligence. I had read Kurzweil’s books and had found them largely ridiculous. However, listening to all the comments at the meeting, from people I respected and admired, forced me to critically examine my own views. While assuming that these AI researchers underestimated humans, had I in turn underestimated the power and promise of current-day AI?

I could go on and on with dueling quotations. In short, what I found is that the field of AI is in turmoil. Either a huge amount of progress has been made, or almost none at all. Either we are within spitting distance of “true” AI, or it is centuries away. AI will solve all our problems, put us all out of a job, destroy the human race, or cheapen our humanity. It’s either a noble quest or “summoning the demon” [Elon Musk].

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