In the context of the lecture series “(Re)thinking Intellectual Property, Fundamental Questions and New Perspectives”, the CEIPI has the pleasure of welcoming on Tuesday April the 16th 2019 at 6 pm, Strasbourg, Building l’Escarpe, 11 rue du Maréchal Juin, auditorium 23, Prof. Daniel Gervais,Director of the Vanderbilt Intellectual Property Program, Faculty Co-Director, LL.M. Program, Vanderbilt University (USA).
The public lecture will focus on the topic: "Big data and Intellectual Property Law". The debate will be moderated by Prof. Christophe Geiger, Director General of CEIPI.
Brief CV:
Daniel Gervais is the Milton R. Underwood Chair in Law at Vanderbilt University, where he is leading the research program on Intellectual Property and the LLM program. He is also full professor at the University of Amsterdam (2017-2019). Until August 2019, he is Chairman of the International Association for the Advancement of Teaching And Research in Intellectual Property (ATRIP). Professor Gervais previously served as acting dean and vice-dean for research of the Common Law Section at the University of Ottawa. He is a member of the bars of Quebec and Ontario, member of the Academy of Europe and of the American Law Institute (elected), where he serves as Associate Reporter of the Restatement of Copyright (First). He is Doctor of Law from the University of Nantes.
A detailed CV (in English) with links to his main publications is available at the following address: works.bepress.com/daniel_gervais/
Abstract:
Professor Gervais will review the application of several IP rights (copyright, patent, sui generis database right, data exclusivity and trade secret) to Big Data. Beyond the protection of software used to collect and process Big Data corpora, copyright’s traditional role is challenged by the relatively unstructured nature of the non-relational (noSQL) databases typical of Big Data corpora. This also impacts the application of the EU sui generis right in databases. Misappropriation (tort-based) or anti-parasitic behaviour protection might apply, where available, to data generated by AI systems that has high but short-lived value. Copyright in material contained in Big Data corpora must also be considered. Exceptions for Text and Data Mining (TDM) are already in place in a number of legal systems and likely to emerge to allow the creation and use of corpora of literary and artistic works, such as texts and images. In the patent field, AI systems using Big Data corpora of patents and scientific literature can be used to expand patent applications. They can also be used to “guess” and disclose future incremental innovation. These developments pose serious doctrinal and normative challenges to the patent system and the incentives it creates in a number of areas, though data exclusivity regimes can fill certain gaps in patent protection for pharmaceutical and chemical products. Finally, trade secret law, in combination with contracts and technological protection measures, can protect data corpora and sets of correlations and insights generated by AI systems.
