The Management and Organization of Innovation
Perhaps most immediately, the rise of general-purpose predictive analytics using large
datasets seems likely to result in a substitution towards capital and away from labor in the
research production process. Many types of R&D and innovation more generally are effectively
problems of labor-intensive search with high marginal cost per search (Evenson and Kislev,
1975, among others). The development of deep learning holds out the promise of sharply
reduced marginal search costs, inducing R&D organizations to substitute away from highlyskilled labor towards fixed cost investments in AI. These investments are likely to improve
performance in existing “search intensive” research projects, as well as to open up new
opportunities to investigate social and physical phenomena that have previously been considered
intractable or even as beyond the domain of systematic scientific and empirical research.
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