In contrast to technological
progress in relatively narrow domains, such as traditional automation and industrial robots, we
argue that those areas of artificial intelligence evolving most rapidly—such as deep learning—
are likely to raise serious challenges in both dimensions.
First, consider the challenge in providing appropriate innovation incentives when an
innovation has potential to drive technological and organizational change across a wide number
of distinct applications. Such “general purpose technologies” (David, 1990; Bresnahan and
Trajtenberg, 1995) often take the form of core inventions that have the potential to significantly
enhance productivity or quality across a wide number of fields or sectors. David’s (1990)
foundational study of the electric motor showed that this invention brought about enormous
technological and organizational change across sectors as diverse as manufacturing, agriculture,
retail, and residential construction.
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