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Abstract:
This contribution reflects on two technologies enabling cumulative innovation – new genomic techniques (NGTs) and machine learning (ML). These broadly applicable enabling technologies illustrate a persistent dilemma in patent policy and the economics of knowledge: How to reconcile the expected incentive effect of patents on knowledge creation with their apparent restrictive effect on knowledge dissemination? After reviewing the theoretical premises and insights from empirical literature, the paper offers preliminary observations on why NGTs and ML, while sharing many similarities, markedly differ in terms of diffusion through their downstream applications. In conclusion, it suggests that compulsory licensing of patents for enabling technologies, such as research tools, should be considered as an instrument for promoting cumulative research and innovation.
