Machine Learning and EU Data-Sharing Practices: Legal Aspects of Machine Learning Training Datasets for AI Systems

Details

Author(s):
Publish Date:
May 11, 2021
Publication Title:
Research Handbook on Big Data Law,
Publisher:
Edward Elgar Publishing
Place of Publication:
Northampton, MA
Editor(s):
  • Roland Vogl
Format:
Book, Section Page(s) 431-452
Citation(s):
  • Mauritz Kop, Machine Learning and EU Data-Sharing Practices: Legal Aspects of Machine Learning Training Datasets for AI Systems, in Roland Vogl, Ed., Research Handbook on Big Data Law, pp. 431-452, Northampton, MA: Edward Elgar Publishing, 2021.
Related Organization(s):

Abstract

This chapter connects the dots between intellectual property and data, data ownership, and data protection. It also provides Artificial Intelligence (AI) & data policy and regulatory recommendations to the EU legislature.

Data sharing is a prerequisite for a successful transatlantic AI ecosystem. This chapter provides solutions for obstacles surrounding data sharing for machine learning purposes.

In an era of exponential innovation, it is critical that the Database Directive, the Copyright Directive and the Trade Secret Directive will be reformed by the EU Commission with the data-driven economy in mind. Articulation of competition law regimes is a better approach than introducing exclusive data property rights. Improved access to data and legal certainty around data and privacy will greatly benefit the growth of the AI ecosystem.

This chapter concludes that embedding norms, standards, principles and values into the architecture of our technology allows regulators to avoid imposing related innovation- and market-stifling regimes.