We suggest that this is likely to lead to a significant substitution away from more routinized
labor-intensive research towards research that takes advantage of the interplay between passively
generated large datasets and enhanced prediction algorithms. At the same time, the potential
commercial rewards from mastering this mode of research are likely to usher in a period of
racing, driven by powerful incentives for individual companies to acquire and control critical
large datasets and application-specific algorithms. We suggest that policies which encourage
transparency and sharing of core datasets across both public and private actors may be critical
tools for stimulating research productivity and innovation-oriented competition going forward.