Project publications

2024

Vizgirda et al. SocialGenPod: Privacy-Friendly Generative AI Social Web Applications with Decentralised Personal Data Stores. In WWW’2024. [pdf]
Zhao R and Zhao J. Perennial semantic data terms of use for decentralized web. In WWW’2024. [pdf]
Wang et al. KOALA Hero Toolkit: A New Approach to Inform Families of Mobile Datafication Risks. In CHI’2024. [pdf]
Wang et al. CHAITok: A Proof-of-Concept System Supporting Children’s Sense of Data Autonomy on Social Media. In CHI’2024. [pdf]
Wang et al. Challenges and opportunities in translating ethical AI principles into practice for children. Nature Machine Intelligence 6(3):265-270 20 Mar 2024. [pdf]

2023

Ramesh et al. Decentralised, Scalable and Privacy-Preserving Synthetic Data Generation. [arxiv]
Zhao et al. Libertas: Privacy-Preserving Computation for Decentralised Personal Data Stores. [arxiv]
Zhao et al. Long-living Service for Cooperative Knowledge Use in Decentralized Data Stores. [arxiv]
Ekambaranathan A, Zhao J and Chalhoub G. ““Navigating the Data Avalanche: Towards Supporting Developers in Developing Privacy-Friendly Children’s Apps”. In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). [pdf]
Ekambaranathan A, Zhao J and Van Kleek M. “How Can We Design Privacy-Friendly Apps for Children? Using a Research through Design Process to Understand Developers’ Needs and Challenges”. CSCW 2023. [pdf]
Stein et al. “‘You are you and the app. There’s nobody else.’: Building Worker-Designed Data Institutions within Platform Hegemony.” Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. 2023. [pdf]
Stein J, Jake ML and Calacci, Dan, “From access to understanding: Collective data governance for workers.” European Labor Law Journal. 2023. [pdf]
Wang et al. 12 Ways to Empower: Designing for Children’s Digital Autonomy. CHI 2023. [pdf]
Wang et al. “Treat me as your friend, not a number in your database”: Co-designing with Children to Cope with Datafication Online [pdf]
Zhao, J. Call for a new data governance structure for datafied childhood. [pdf]

2022

Kollnig et al. Before and after GDPR: tracking in mobile apps. Internet Policy Review, 10(4).[pdf][Journal]
Wang et al. ‘Don’t make assumptions about me!’: Understanding Children’s Perception of Datafication Online. CSCW’22. [pdf][Journal]
Kollnig et al. Goodbye tracking? Impact of iOS app tracking transparency and privacy labels. In Proc. of FAccT’22 [pdf][Conference]
Wang et al. Informing Age-Appropriate AI: Examining Principles and Practices of AI for Children. Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. 536(1-29). pdf [presentation][Conference]
Veale et al. Fortifying the Algorithmic Management Provisions in the Proposed Platform Work Directive. [pdf][Report]
EWADA’s Response to DCMS Consultation on Online Safety Bill. June 2022. [pdf][Report]
A suits of essays published by our team members during our inaugural colloquium with the GoodEnough College in March 2022[link][Report]
EWADA’s Response to CMA Consultation on Mobile Ecosystems.February 2022[link][Report]

2021

Wang et al. Protection or punishment? relating the design space of parental control apps and perceptions about them to support parenting for online safety. CSCW’21. [pdf][Journal]
Agrawal et al. Exploring design and governance challenges in the development of privacy-preserving computation. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 68 (1-3)[pdf][Conference]
Kollnig et al. Are iPhones Really Better for Privacy? Comparative Study of iOS and Android Apps. Proceedings on Privacy Enhancing Technologies. 2022. 2(6-24)[pdf][Conference]
EWADA’s Response to DCMS Consultation on Reformation of the UK’s Data Protection Regime. November 2021[pdf][Report]

Background publications

Binns et al. Third party tracking in the mobile ecosystem. In Proceedings of the 10th ACM Conference on Web Science, pages 23–31, 2018. pdf
Van Kleek et al. Iot refine: Making smart home devices accountable for their data harvesting practices. In Living in the Internet of Things: Cybersecurity of the IoT Conference. Living in the Internet of Things: Cybersecurity of the IoT Conference, 2019. pdf
Zhao et al. I make up a silly name’ understanding children’s perception of privacy risks online. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pages 1–13, 2019. pdf

Carissa Véliz. The internet and privacy. 2019. pdf
Agrawal et al. Quotient: two-party secure neural network training and prediction. In Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, pages 1231–1247, 2019. pdf

Wachter et al. Why a right to explanation of automated decision- making does not exist in the general data protection regulation. International Data Privacy Law, 7(2):76–99, 2017. pdf
Wachter et al. Counterfactual explanations without opening the black box: Automated decisions and the GDPR. Harv. JL & Tech., 31:841, 2017. pdf
Binns et al. ’It’s reducing a human being to a percentage’ perceptions of justice in algorithmic decisions. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pages 1–14, 2018. pdf
Binns et al. Like trainer, like bot? inheritance of bias in algorithmic content moderation. In International Conference on Social Informatics, pages 405–415. Springer, 2017. pdf
Wachter and Mittelstadt. A right to reasonable inferences: re-thinking data protection law in the age of big data and AI. Colum. Bus. L. Rev., page 494, 2019.pdf

Carissa Véliz. Medical privacy and big data: A further reason in favour of public universal healthcare coverage. In: Philosophical Foundations of Medical Law. Oxford (UK): Oxford University Press; 2019. Wellcome Trust–Funded Monographs and Book Chapters. 2019.link
Carissa Véliz. Three things digital ethics can learn from medical ethics. Nature Electronics, 2(8):316–318, 2019.link