Automation and the Law (10th LSGL Summer School, FGV Rio, 25-29 July 2022) (Syllabus)

Giancarlo Frosio (University of Turin, Nexa Center, Center for International Intellectual Property Studies, Stanford CIS)

This syllabus includes materials specifically designed for the course Automation and the Law at the 10th LSGL Summer School. It is a resource aiming at blending together international, European and US legislation, case law, and doctrinal pieces. It is intended to be a resource that might serve as a reference for further in depth review of the topics touched upon during the training program. This syllabus is a work in progress and will be updated in due course.

3 Module 2 - Automation and Data 3 Module 2 - Automation and Data

3.1. Ryan Calo, Peeping HALs: Making Sense of Artificial Intelligence and Privacy, 2(3) European Journal of Legal Studies 168-192 (2010)

Ryan Calo, Peeping HALs: Making Sense of Artificial Intelligence and Privacy, 2(3) European Journal of Legal Studies 168-192 (2010)

3.2. Kate Crawford, Jason Schultz, J., Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms, 55 Boston College of Law Review 93-128 (2014)

Kate Crawford, Jason Schultz, J., Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms, 55 Boston College of Law Review 93-128 (2014)

3.3. Yotaro Okazaki, Implications of Big Data for Customs - How It Can Support Risk Management Capabilities, WCO, 2017

Yotaro Okazaki, Implications of Big Data for Customs - How It Can Support Risk Management Capabilities, WCO, 2017

3.4. Jean-Marc Deltorn, La Protection des Donnes Personelles Face Aux Algorithmes Predictifs, 12 RDLF (2017)

Jean-Marc Deltorn, La Protection des Donnes Personelles Face Aux Algorithmes Predictifs, 12 RDLF (2017)

3.5 2.1 - Text and Data Mining 3.5 2.1 - Text and Data Mining

3.5.1. Christophe Geiger, Giancarlo Frosio, Oleksandr Bulayenko, The Exception for Text and Data Mining (TDM) in the proposed Directive on Copyright in the Digital Single Market: Legal Aspect, In-Depth Analysis for the Directorate-General for Internal Policies of the Union, Policy Department Citizens Rights and Constitutional Affairs, European Parliament, PE 604.941 (February 2018)

Christophe Geiger, Giancarlo Frosio, Oleksandr Bulayenko, The Exception for Text and Data Mining (TDM) in the proposed Directive on Copyright in the Digital Single Market: Legal Aspect, In-Depth Analysis for the Directorate-General for Internal Policies of the Union, Policy Department Citizens Rights and Constitutional Affairs, European Parliament, PE 604.941 (February 2018)

3.5.2. Andres Guadamuz and Diane Cabell, Data Mining in UK Higher Education Institutions: Law and Policy, 4(1) Queen Mary Intellectual Property Review 3-29 (2014)

Andres Guadamuz and Diane Cabell, Data Mining in UK Higher Education Institutions: Law and Policy, 4(1) Queen Mary Intellectual Property Review 3-29 (2014)

3.5.3. Maarteen Truyens, Patric Van Eecke, "Legal aspects of text mining", 30(2) Computer Law & Security Review 2182 (2014).

Maarteen Truyens, Patric Van Eecke, "Legal aspects of text mining", 30(2) Computer Law & Security Review 2182 (2014).

Is There A "Right To Explanation" for Machine Learning in the GDPR?

3.6.3. Lilian Edwards and Michael Veale, Slave to the Algorithm? Why a 'Right to an Explanation' Is Probably Not the Remedy You Are Looking For, 16 Duke Law & Technology Review 18 (2017).

Lilian Edwards and Michael Veale, Slave to the Algorithm? Why a 'Right to an Explanation' Is Probably Not the Remedy You Are Looking For, 16 Duke Law & Technology Review 18 (2017).

3.7. Michael Kearns, Data Intimacy, Machine Learning, and Consumer Privacy (Penn Law CTIC Research Paper, 2018)

Michael Kearns, Data Intimacy, Machine Learning, and Consumer Privacy (Penn Law CTIC Research Paper, 2018)

3.8. Brenda Simon and Ted Sichelman, Data-generating patents, 111 Nw. U. L. Rev. 377 (2016)

Brenda Simon and Ted Sichelman, Data-generating patents, 111 Nw. U. L. Rev. 377 (2016)