649 citations · 2.5k across the 31 of their papers we have counts for
37 papers
Respectful Things: Adding Social Intelligence to 'Smart' Devices
Max Van Kleek, William Seymour, Reuben Binns +1
In this paper, we propose that the idea of devices respecting their end-users may serve as a strong design goal for highly personal and intimate smart devices. We ask what respect…
Language Models Change Facts Based on the Way You Talk
Matthew Kearney, Reuben Binns, Yarin Gal
Large language models (LLMs) are increasingly being used in user-facing applications, from providing medical consultations to job interview advice. Recent research suggests that th…
Not Even Nice Work If You Can Get It; A Longitudinal Study of Uber's Algorithmic Pay and Pricing
Reuben Binns, Jake Stein, Siddhartha Datta +2
Ride-sharing platforms like Uber market themselves as enabling `flexibility' for their workforce, meaning that drivers are expected to anticipate when and where the algorithm will…
Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
Alexandra Olteanu, Su Lin Blodgett, Agathe Balayn +7
In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or computational methods are correctly…
Access Denied: Meaningful Data Access for Quantitative Algorithm Audits
Juliette Zaccour, Reuben Binns, Luc Rocher
Independent algorithm audits hold the promise of bringing accountability to automated decision-making. However, third-party audits are often hindered by access restrictions, forcin…
Governance of Generative AI in Creative Work: Consent, Credit, Compensation, and Beyond
Lin Kyi, Amruta Mahuli, M. Six Silberman +3
Since the emergence of generative AI, creative workers have spoken up about the career-based harms they have experienced arising from this new technology. A common theme in these a…
Reputation Management in the ChatGPT Era
Lilian Edwards, Reuben Binns
Generative AI systems often generate outputs about real people, even when not explicitly prompted to do so. This can lead to significant reputational and privacy harms, especially…
The Interaction Layer: An Exploration for Co-Designing User-LLM Interactions in Parental Wellbeing Support Systems
Sruthi Viswanathan, Seray Ibrahim, Ravi Shankar +3
Parenting brings emotional and physical challenges, from balancing work, childcare, and finances to coping with exhaustion and limited personal time. Yet, one in three parents neve…
"Diversity is Having the Diversity": Unpacking and Designing for Diversity in Applicant Selection
Neil Natarajan, Sruthi Viswanathan, Reuben Binns +1
When selecting applicants for scholarships, universities, or jobs, practitioners often aim for a diverse cohort of qualified recipients. However, differing articulations, construct…
Unlawful Proxy Discrimination: A Framework for Challenging Inherently Discriminatory Algorithms
Hilde Weerts, Aislinn Kelly-Lyth, Reuben Binns +1
Emerging scholarship suggests that the EU legal concept of direct discrimination - where a person is given different treatment on grounds of a protected characteristic - may apply…
Libertas: Privacy-Preserving Collective Computation for Decentralised Personal Data Stores
Rui Zhao, Naman Goel, Nitin Agrawal +7
Data and data processing have become an indispensable aspect for our society. Insights drawn from collective data make invaluable contribution to scientific and societal research a…
We Are Not There Yet: The Implications of Insufficient Knowledge Management for Organisational Compliance
Thomas Şerban von Davier, Konrad Kollnig, Reuben Binns +2
Since GDPR went into effect in 2018, many other data protection and privacy regulations have been released. With the new regulation, there has been an associated increase in indust…
Trust Explanations to Do What They Say
Neil Natarajan, Reuben Binns, Jun Zhao +1
How much are we to trust a decision made by an AI algorithm? Trusting an algorithm without cause may lead to abuse, and mistrusting it may similarly lead to disuse. Trust in an AI…
The Cost of the GDPR for Apps? Nearly Impossible to Study without Platform Data
Konrad Kollnig, Reuben Binns
A recently published pre-print titled 'GDPR and the Lost Generation of Innovative Apps' by Janßen et al. observes that a third of apps on the Google Play Store disappeared from thi…
Respect as a Lens for the Design of AI Systems
William Seymour, Max Van Kleek, Reuben Binns +1
Critical examinations of AI systems often apply principles such as fairness, justice, accountability, and safety, which is reflected in AI regulations such as the EU AI Act. Are su…
Goodbye Tracking? Impact of iOS App Tracking Transparency and Privacy Labels
Konrad Kollnig, Anastasia Shuba, Max Van Kleek +2
Tracking is a highly privacy-invasive data collection practice that has been ubiquitous in mobile apps for many years due to its role in supporting advertising-based revenue models…
Tracking on the Web, Mobile and the Internet-of-Things
Reuben Binns
`Tracking' is the collection of data about an individual's activity across multiple distinct contexts and the retention, use, or sharing of data derived from that activity outside…
Before and after GDPR: tracking in mobile apps
Konrad Kollnig, Reuben Binns, Max Van Kleek +4
Third-party tracking, the collection and sharing of behavioural data about individuals, is a significant and ubiquitous privacy threat in mobile apps. The EU General Data Protectio…
Are iPhones Really Better for Privacy? Comparative Study of iOS and Android Apps
Konrad Kollnig, Anastasia Shuba, Reuben Binns +2
While many studies have looked at privacy properties of the Android and Google Play app ecosystem, comparatively much less is known about iOS and the Apple App Store, the most wide…
How Could Equality and Data Protection Law Shape AI Fairness for People with Disabilities?
Reuben Binns, Reuben Kirkham
This article examines the concept of 'AI fairness' for people with disabilities from the perspective of data protection and equality law. This examination demonstrates that there i…
A Fait Accompli? An Empirical Study into the Absence of Consent to Third-Party Tracking in Android Apps
Konrad Kollnig, Reuben Binns, Pierre Dewitte +5
Third-party tracking allows companies to collect users' behavioural data and track their activity across digital devices. This can put deep insights into users' private lives into…
Exploring Design and Governance Challenges in the Development of Privacy-Preserving Computation
Nitin Agrawal, Reuben Binns, Max Van Kleek +2
Homomorphic encryption, secure multi-party computation, and differential privacy are part of an emerging class of Privacy Enhancing Technologies which share a common promise: to pr…
Decentralized Privacy-Preserving Proximity Tracing
Carmela Troncoso, Mathias Payer, Jean-Pierre Hubaux +31
This document describes and analyzes a system for secure and privacy-preserving proximity tracing at large scale. This system, referred to as DP3T, provides a technological foundat…
Strangers in the Room: Unpacking Perceptions of 'Smartness' and Related Ethical Concerns in the Home
William Seymour, Reuben Binns, Petr Slovak +2
The increasingly widespread use of 'smart' devices has raised multifarious ethical concerns regarding their use in domestic spaces. Previous work examining such ethical dimensions…