Benedict Evans, a tech analyst whose newsletter is required reading for those who follow the industry, made an interesting point this week. He had, he said, been talking to generalist journalists who “were still under the impression that ChatGPT was a trivial parlour trick and the whole thing was about as interesting as a new iPhone app”. On the other hand, he continued, “most people in tech are walking around slowly, holding on to the top of their head with both hands to stop it flying off. But within that, I think we can see a range of attitudes.”
We certainly can – on a spectrum ranging from the view that this “generative AI” is going to be the biggest bonanza since the invention of the wheel, to fears that it augurs an existential risk to humanity, and numerous opinions in between. Seeking a respite from the firehose of contradictory commentary, I suddenly remembered an interview that Steve Jobs – the nearest thing to a visionary the tech industry has ever had – gave in 1990, and dug it out on YouTube.
In it he talks about a memory he had of reading an article in Scientific American when he was 12 years old. It was a report of how someone had measured the efficiency of locomotion for a number of species on planet Earth – “how many kilocalories did they expend to get from point A to point B. And the condor won – came in at the top of the list, surpassed everything else; and humans came in about a third of the way down the list, which was not such a great showing for the ‘crown of creation’.
“But then somebody there had the imagination to test the efficiency of a human riding a bicycle. A human riding a bicycle blew away the condor, all the way to the top of the list. And it made a really big impression on me – that we humans are tool-builders, and that we can fashion tools that amplify these inherent abilities that we have to spectacular magnitudes.
“And so for me,” he concluded, “a computer has always been a bicycle of the mind – something that takes us far beyond our inherent abilities. And I think we’re just at the early stages of this tool – very early stages – and we’ve come only a very short distance, and it’s still in its formation, but already we’ve seen enormous changes, [but] that’s nothing to what’s coming in the next 100 years.”
Well, that was 1990 and here we are, three decades later, with a mighty powerful bicycle. Quite how powerful it is becomes clear when one inspects how the technology (not just ChatGPT) tackles particular tasks that humans find difficult.
Writing computer programs, for instance.
Last week, Steve Yegge, a renowned software engineer who – like all uber-geeks – uses the ultra-programmable Emacs text editor, conducted an instructive experiment. He typed the following prompt into ChatGPT: “Write an interactive Emacs Lisp function that pops to a new buffer, prints out the first paragraph of A Tale of Two Cities, and changes all words with ‘i’ in them red. Just print the code without explanation.”
ChatGPT did its stuff and spat out the code. Yegge copied and pasted it into his Emacs session and published a screenshot of the result. “In one shot,” he writes, “ChatGPT has produced completely working code from a sloppy English description! With voice input wired up, I could have written this program by asking my computer to do it. And not only does it work correctly, the code that it wrote is actually pretty decent Emacs Lisp code. It’s not complicated, sure. But it’s good code.”
Ponder the significance of this for a moment, as tech investors such as Paul Kedrosky are already doing. He likens tools such as ChatGPT to “a missile aimed, however unintentionally, directly at software production itself. Sure, chat AIs can perform swimmingly at producing undergraduate essays, or spinning up marketing materials and blog posts (like we need more of either), but such technologies are terrific to the point of dark magic at producing, debugging, and accelerating software production quickly and almost costlessly.”
Since, ultimately, our networked world runs on software, suddenly having tools that can write it – and that could be available to anyone, not just geeks – marks an important moment. Programmers have always seemed like magicians: they can make an inanimate object do something useful. I once wrote that they must sometimes feel like Napoleon – who was able to order legions, at a stroke, to do his bidding. After all, computers – like troops – obey orders. But to become masters of their virtual universe, programmers had to possess arcane knowledge, and learn specialist languages to converse with their electronic servants. For most people, that was a pretty high threshold to cross. ChatGPT and its ilk have just lowered it.
What I’ve been reading
Write on
A masterly reflective essay on writing by Helen Lewis on her Substack blog.
Meeting of minds
An insightful analysis of the meeting between Xi Jinping and Putin by Nathan Gardels in Noema magazine.
Tall tales
The Monster Discloses Himself is an astute essay on the allure of conspiracy theory in the Hedgehog Review by Phil Christman.