Sixty years ago, in an era of computer mainframes and slide rules, J C R Licklider of the Defense Advanced Research Projects Agency (DARPA) outlined a bold vision of a mutually beneficial human-computer symbiosis, a partnership in which both humans and machines positively benefit Both of us have developed technologies that fit this template: lab automation for drug discovery, software for optimizing engineering design, and improved coordination and planning tools for military operators The critical insight was that the automation couldn't replace the cognitive breadth of a human copilot dealing with uncertainty and ambiguity, but could perform better at many tasks where humans struggled, such as landing with a failed engine where controlling the flight path to preserve every watt of energy counts, something once believed to be uniquely suited to humans Even though piloting is considered highly skilled because of the intensive human training required, the task allocation model underpinning the concept of human-machine teaming is unlikely to carry over to endeavors with more ambiguous notions of how tasks relate to "good" outcomes, or to problems in which learning what the tasks or outcomes should even be is central to making progress
Can AI Make Your Job More Interesting?