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The Ethics of Agonistic Machine Learning (w/ Mireille Hildebrandt)

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Centre for Ethics

Room 200, Second Floor, Larkin Building, 15 Devonshire Place

Toronto, ON, Ontario M5S 1H8

Canada

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What do we mean when we say that machines learn? What is the difference that makes a difference between human learning and machine learning? In my talk I will discuss the nature of machine learning (ML), including a series of design decisions that inform ML research designs and the trade-offs they incorporate. I will argue that these trade-offs have real world implications that require the participation of those who will suffer or enjoy the consequences of real world ML applications. Building on Mouffe’s democratic theory and Rip’s constructive technology assessment, I will argue for agonistic or adversarial ML as the only viable way to ensure that ML contributes to human and societal flourishing.

Mireille Hildebrandt
Law and Technology, Vrije Universiteit Brussels
Computing & Information Sciences, Radboud University Nijmegen

Tue, Feb 6, 2018
04:00 PM - 06:00 PM
Centre for Ethics, University of Toronto
Rm 200, Larkin Building

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Centre for Ethics

Room 200, Second Floor, Larkin Building, 15 Devonshire Place

Toronto, ON, Ontario M5S 1H8

Canada

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