Since GDPR went into effect in 2018, many other data protection and priv...
A recently published pre-print titled 'GDPR and the Lost Generation of
I...
Critical examinations of AI systems often apply principles such as fairn...
Tracking is a highly privacy-invasive data collection practice that has ...
`Tracking' is the collection of data about an individual's activity acro...
Third-party tracking, the collection and sharing of behavioural data abo...
While many studies have looked at privacy properties of the Android and
...
This article examines the concept of 'AI fairness' for people with
disab...
Third-party tracking allows companies to collect users' behavioural data...
Homomorphic encryption, secure multi-party computation, and differential...
This document describes and analyzes a system for secure and
privacy-pre...
The increasingly widespread use of 'smart' devices has raised multifario...
Connected devices in the home represent a potentially grave new privacy
...
A distinction has been drawn in fair machine learning research between
`...
Many people struggle to control their use of digital devices. However, o...
Many individuals are concerned about the governance of machine learning
...
Third party tracking allows companies to identify users and track their
...
In this short paper, we consider the roles of HCI in enabling the better...
Equating users' true needs and desires with behavioural measures of
'eng...
Third-party networks collect vast amounts of data about users via web si...
Calls for heightened consideration of fairness and accountability in
alg...
Data-driven decision-making consequential to individuals raises importan...
What does it mean for a machine learning model to be `fair', in terms wh...
The internet has become a central medium through which `networked public...