NOBODY LIKES AN I-told-you-so. But before Microsoft’s Bing started cranking out creepy love letters; before Meta’s Galactica spewed racist rants; before ChatGPT began writing such perfectly decent college essays that some professors said, “Screw it, I’ll just stop grading”; and before tech reporters sprinted to claw back claims that AI was the future of search, maybe the future of everything else, too, Emily M. Bender co-wrote the octopus paper.
Bender is a computational linguist at the University of Washington. She published the paper in 2020 with fellow computational linguist Alexander Koller. The goal was to illustrate what large language models, or LLMs—the technology behind chatbots like ChatGPT—can and cannot do. The setup is this:
Say that A and B, both fluent speakers of English, are independently stranded on two uninhabited islands. They soon discover that previous visitors to these islands have left behind telegraphs and that they can communicate with each other via an underwater cable. A and B start happily typing messages to each other.
Meanwhile, O, a hyperintelligent deep-sea octopus who is unable to visit or observe the two islands, discovers a way to tap into the underwater cable and listen in on A and B’s conversations. O knows nothing about English initially but is very good at detecting statistical patterns. Over time, O learns to predict with great accuracy how B will respond to each of A’s utterances.
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