The history of AI is often told as the story of machines getting smarter over time. What’s lost is the human element in the narrative, how intelligent machines are designed, trained, and powered by human minds and bodies.
At 10:30pm on 29 October 1969, a graduate student at UCLA sent a two-letter message from an SDS Sigma 7 computer to another machine a few hundred miles away at the Stanford Research Institute in Menlo Park. In histories of the internet, this moment is celebrated as ushering in a new age of online communication. What is often forgotten, however, is that underlying the technical infrastructure of the ARPANET was a radical vision for a future of human-machine symbiosis developed by a man named J.C.R. Licklider.
Licklider, who had a background in psychology, became interested in computers in the late 1950s when working at a small consulting firm. He was interested in how these new machines could amplify humanity’s collective intelligence, and began to conduct research into the burgeoning field of AI. When he reviewed the existing literature, he found that programmers aimed to “teach” these machines how to perform pre-existing human activities, such as chess or language translation, with greater aptitude and efficiency than humans.
This conception of machine intelligence didn’t sit well with Licklider. The problem, for him, was that the existing paradigm saw humans and machines as being intellectually equivalent beings. Licklider believed that, in fact, humans and machines were fundamentally different in their cognitive capacities and strengths.
Instead of having computers imitate human intellectual activities, Licklider proposed an approach in which humans and machines would collaborate, each making use of their particular advantage. He suggested that this strategy would shift the focus from competition (like computer-versus-human chess matches), and facilitate previously unimaginable forms of intelligent activity.
In a 1960 paper entitled “Man-Machine Symbiosis,” Licklider spelled out his idea. “The hope is that in not too many years, human brains and computing machines will be coupled together very tightly, and that the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.”
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