- February 22, 2019
- By Ben Shneiderman
Some of the biggest-thinking researchers working to develop artificial intelligence may be thinking a little too big and impeding real innovation, says Ben Shneiderman, a Distinguished University Professor in the Department of Computer Science and the University of Maryland Institute for Advanced Computer Studies.
In an essay published yesterday in The Conversation, Shneiderman argues AI development should focus on solving tangible problems rather than projects to build autonomous intelligences, which could fail to pan out just as did grand, futile schemes of centuries past:
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.
Read the full essay here.