The Best Intelligence Is Cyborg Intelligence
The best services arise from the combination of machine and human intelligences. As algorithmic entities explode across the web, humans remain central to their operation. Automation only goes so far and for all Watson’s Jeopardy wins, there are still many, many tasks on which computers are terrible and humans are effortlessly amazing. Like understanding language, say, or knowing what’s happening in a photograph. We noted this phenomenon in our work on Google Maps, which has a team of thousands of humans who hand correct every single map.
There is an analogy to be made to one of Google’s other impressive projects: Google Translate. What looks like machine intelligence is actually only a recombination of human intelligence. Translate relies on massive bodies of text that have been translated into different languages by humans; it then is able to extract words and phrases that match up. The algorithms are not actually that complex, but they work because of the massive amounts of data (i.e. human intelligence) that go into the task on the front end.
Google Maps has executed a similar operation. Humans are coding every bit of the logic of the road onto a representation of the world so that computers can simply duplicate (infinitely, instantly) the judgments that a person already made. The Times story is well worth reading for its catalog of similar operations at other companies like Twitter, Apple, IBM, and some startups. The point is not that machines are not powerful or that humans are irreplaceable in some fixed sense. The point is that the best services are cyborg: they arise from the combination of machine and human intelligences. As Manfred Clynes and Nathan Kline, the co-coiners of the term “cyborg,” wrote in 1960, “The purpose of the Cyborg, as well as his own homeostatic systems, is to provide an organizational system in which such robot-like problems are taken care of automatically and unconsciously, leaving man free to explore, to create, to think, and to feel.” Fifty-three years later, I think the jury is still out on whether or not his initial hope was correct.