suggest that artificial intelligence may ultimately have applications across a very wide range.
From the perspective of the economics of innovation (among others, Bresnahan and Trajtenberg
(1995)), there is an important distinction between the problem of providing innovation incentives
to develop technologies with a relatively narrow domain of application, such robots purposebuilt for narrow tasks, versus technologies with a wide—advocates might say almost limitless—
domain of application, as may be true of the advances in neural networks and machine learning
often referred to as “deep learning.” As such, a first question to be asked is the degree to which
developments in artificial intelligence are not simply examples of new technologies, but rather
may be the kinds of “general purpose technologies” (hereafter GPTs) that have historically been
such influential drivers of long-term technological progress.
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