649 citations · 1.4k across the 5 of their papers we have counts for
7 papers · 1 filter
Eavesdropping Whilst You're Shopping: Balancing Personalisation and Privacy in Connected Retail Spaces
Vasilios Mavroudis, Michael Veale
Physical retailers, who once led the way in tracking with loyalty cards and `reverse appends', now lag behind online competitors. Yet we might be seeing these tables turn, as many…
Algorithms that Remember: Model Inversion Attacks and Data Protection Law
Michael Veale, Reuben Binns, Lilian Edwards
Many individuals are concerned about the governance of machine learning systems and the prevention of algorithmic harms. The EU's recent General Data Protection Regulation (GDPR) h…
Blind Justice: Fairness with Encrypted Sensitive Attributes
Niki Kilbertus, Adrià Gascón, Matt J. Kusner +3
Recent work has explored how to train machine learning models which do not discriminate against any subgroup of the population as determined by sensitive attributes such as gender…
Some HCI Priorities for GDPR-Compliant Machine Learning
Michael Veale, Reuben Binns, Max Van Kleek
In this short paper, we consider the roles of HCI in enabling the better governance of consequential machine learning systems using the rights and obligations laid out in the recen…
Enslaving the Algorithm: From a "Right to an Explanation" to a "Right to Better Decisions"?
Lilian Edwards, Michael Veale
As concerns about unfairness and discrimination in "black box" machine learning systems rise, a legal "right to an explanation" has emerged as a compellingly attractive approach fo…
Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making
Michael Veale, Max Van Kleek, Reuben Binns
Calls for heightened consideration of fairness and accountability in algorithmically-informed public decisions---like taxation, justice, and child protection---are now commonplace.…