The impact of increasing returns on knowledge and big data: from Adam Smith and Allyn Young to the age of machine learning and digital platforms

Allyn Young's concept of increasing returns (not to be confused with static, equilibrium constructs of economies of scale and increasing returns to scale) is applied to analyse how and why increasing returns arise in the production (generation) and use (application) of knowledge and big data, thereby driving economic growth and progress. Knowledge is chosen as our focus because it is said to be our most powerful engine of production, and big data are included to make the analysis more complete and recent. We analyse four mechanisms or sources of increasing returns in the production of knowledge, and four in the use of knowledge. Turning to big data, we analyse increasing returns in the functioning of digital platforms and increasing returns in machine learning from gigantic amounts of training data. Concluding remarks concern some key differences between big data and knowledge, some policy implications, and some of the social negative impacts from the ways in which big data are being used.