The Conversation
By Ben Shneiderman, Founding Director of Human-Computer Interaction Lab at University of Maryland
Artificial intelligence researchers and engineers have spent a lot of effort trying to build machines that look like humans and operate largely independently. Those tempting dreams have distracted many of them from where the real progress is already happening: in systems that enhance – rather than replace – human capabilities. To accelerate the shift to new ways of thinking, AI designers and developers could take some lessons from the missteps of past researchers.
For example, alchemists, like Isaac Newton, pursued ambitious goals such as converting lead to gold, creating a panacea to cure all diseases, and finding potions for immortality. While these goals are alluring, the charlatans pursuing them may have secured princely financial backing that would have been better used developing modern chemistry.
Equally optimistically, astrologers believed they could understand human personality based on birthdates and predict future events by studying the positions of the stars and planets. These promises over the past thousand years often received kingly endorsement, possibly slowing the work of those who were adopting scientific methods that eventually led to astronomy.
As alchemy and astrology evolved, the participants became more deliberate and organized – what might now be called more scientific – about their studies. That shift eventually led to important findings in chemistry, such as those by Lavoisier and Priestley in the 18th century. In astronomy, Kepler and Newton himself made significant findings in the 17th and 18th centuries. A similar turning point is coming for artificial intelligence. Bold innovators are putting aside tempting but impractical dreams of anthropomorphic designs and excessive autonomy. They focus on systems that restore, rely on, and expand human control and responsibility.