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GovTechTalks: Algorithmic Decision-Making

When:Th 18-02-2021 12:00 - 13:00
Where:Online

This online and interdisciplinary talks series on digital government and society will take place twice a month on Thursdays at 12.00 CET. Registration is required and is free. The events will be widely publicized on social media and through different academic networks. Each session will include two invited speakers who will present their research and engage with the audience’s questions.

Organizer: Prof. dr. Sofia Ranchordas

Seminar 18 February 2021, 12 PM CET: Algorithmic Decision-Making

Invited Speakers:

  • Jennifer Cobbe (Research Associate and Affiliated Lecturer Computer Science and Technology, University of Cambridge)
  • Frederik Zuiderveen Borgesius (Professor ICT and Law, Radboud University Nijmegen)

Jennifer Cobbe

Title: Confronting the Algorithmic State

Abstract
Algorithmic systems are increasingly used in the public sector, with serious questions about the priorities and values they encode. How can we promote public accountability and ensure that legal standards, human rights, and fundamentals of good government are prioritised in automated decision-making?

Jennifer Cobbe
Bio

Dr Jennifer Cobbe is a Research Associate and Affiliated Lecturer in the Department of Computer Science and Technology (Computer Laboratory) at the University of Cambridge, where she is part of the Compliant and Accountable Systems research group. She holds a PhD in Law and an LLM in Law and Governance from Queen’s University, Belfast. Jennifer is generally interested in critical interdisciplinary work on law, technology and society – the socio-political power of tech companies, the role of their business models and ideological underpinnings in transforming society, and the structural conditions produced through new and emerging technologies.

Frederik Zuiderveen Borgesius

Title: 'Algorithmic Decision-Making, and European Non-Discrimination Law'

Abstract
The talk shows that algorithmic decision-making could lead to indirect discrimination, for instance harming people with a certain ethnicity. Indirect discrimination occurs when a practice is neutral at first glance, but ends up discriminating against people with a protected characteristic, such as ethnicity. In principle, non-discrimination law prohibits indirect discrimination. The talk also shows, however, that non-discrimination law has flaws when applied to algorithmic decision-making.’

Frederik Zuiderveen Borgesius

Bio
Prof Frederik Zuiderveen Borgesius is Professor ICT and Law at Radboud University Nijmegen, where he is affiliated with the interdisciplinary research hub on Security, Privacy, and Data Governance: the iHub. His research interests include privacy, data protection, and discrimination, especially in the context of new technologies.