The Impact of Artificial Intelligence on Innovation

Abstract

The current economy's efficiency may be greatly improved by artificial intelligence. We distinguish between automation-oriented applications like robotics and the potential for recent developments in "deep learning" to serve as a general-purpose method of invention, finding strong evidence of a "shift" in the importance of application-oriented learning research since 2009. However, it may have an even larger impact by serving as a new general-purpose "method of invention" that can reshape the nature of the innovation process and the organization of R&D. We suggest that this will likely result in a significant shift away from routine, labor-intensive research and toward research that makes use of the interaction between improved prediction algorithms and passively generated large datasets. In addition, strong incentives for specific businesses to acquire and control crucial large datasets and application-specific algorithms will likely usher in a period of racing as a result of the potential commercial rewards of mastering this method of research. We suggest that in the future, policies that promote transparency and the sharing of core datasets between public and private actors may be essential for boosting research productivity and encouraging innovation-oriented competition.