Machine Data: market and analytics

Giacomo Calzolari, Anatole Cheysson and Riccardo Rovatti

No 17842, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: Recent technological developments in ICT and Artificial Intelligence allow extracting valuable information from data that machines generate with production, machine data (MD). Although possibly more valuable than personal data, the growing market for MD and its analytics may suffer from several issues, such as datasets fragmented into many small data-producers, externalities as with non-rival information and fuzzy property rights. We combine these market elements with critical properties that we derive from actual Machine Learning algorithms for analytics. We explore how and to what extent a data aggregator can operate, contracting with different data producers to share data and analytics. We identify conditions that impact the market organization for MD, such as producers' heterogeneity, their preference for anonymity, and the intensity of competition in final markets.

Date: 2023-01
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