Data and their processing have become an indispensable aspect for our society. Insights drawn from collective data make invaluable contribution to scientific, societal and communal research and business. However, there are increasing worries about privacy issues and data misuse, prompting the emergence of decentralised personal data stores (PDS) like Solid. However, existing PDS frameworks face challenges in ensuring data privacy when performing collective computation to combine data from multiple users. At a glance, Secure Multi-Party Computation (MPC) offers input secrecy protection while performing collective computation without relying on any single party. However, issues emerge when directly applying MPC in the context of PDS, particularly due to key factors like autonomy and decentralisation. In this work, we discuss the essence of this issue, identify the potential solution, and introduce a modular system architecture, Libertas, to integrate MPC with PDS like Solid, without requiring protocol-level changes. We introduce the paradigm shift from an 'omniscient' view to individual-based, user-centric view of trust and security, and discuss the threat model of Libertas. Two realistic use cases for collaborative data processing are used for evaluation, both for technical feasibility and empirical benchmark, highlighting its effectiveness in empowering gig workers and generating differentially private synthetic data. The results of our experiments underscore Libertas' linear scalability and provide valuable insights into compute optimisations, thereby advancing the state-of-the-art in privacy-preserving data processing practices. By offering practical solutions for maintaining both individual autonomy and privacy in collaborative data processing environments, Libertas contributes significantly to the ongoing discourse on privacy protection in data-driven decision-making contexts.

The growing adoption of smart devices has fuelled privacy concerns, and prior research has highlighted the privacy of bystanders: individuals who are subjected to the smart device use of others. Most of this research has focused on households in Western contexts (i.e., Europe and North America), but few studies have explored the design challenges of protecting bystanders, and even fewer have explored these in Muslim Arab Middle Eastern settings, such as Jordan. We conduct 44 interviews with users (i.e., families, domestic workers), local and international business leaders, and smart device designers to explore design challenges for privacy protection in the Jordanian context. Our analysis highlights the importance of considering contextual influences and power dynamics, localization and design guidelines, innovative technologies, awareness to design, and regulation. This paper concludes with recommendations for technical, social, business, and legal interventions to improve data protection design of smart devices in Jordan.

Information asymmetries create extractive, often harmful relationships between platform workers (e.g., Uber or Deliveroo drivers) and their algorithmic managers. Recent HCI studies have put forward more equitable platform designs but leave open questions about the social and technical infrastructures required to support them without the cooperation of platforms. We conducted a participatory design study in which platform workers deconstructed and re-imagined Uber’s schema for driver data. We analyzed the data structures and social institutions participants proposed, focusing on the stakeholders, roles, and strategies for mitigating conflicting interests of privacy, personal agency, and utility. Using critical theory, we reflected on the capability of participatory design to generate bottom-up collective data infrastructures. Based on the plurality of alternative institutions participants produced and their aptitude to navigate data stewardship decisions, we propose user-configurable tools for lightweight data institution building, as an alternative to redesigning existing platforms or delegating control to centralized trusts.

Smart homes continue to raise concerns about privacy and encroachment of businesses into intimate spaces. Prior research has focused on families and device owners in western contexts (Europe and North America), and has identified the importance of bystanders: individuals who are subjected to smart device use of others. Given the cultural and contextual aspects of accommodating bystanders, we identify a gap where bystanders in non-western societies have been insufficiently researched. To address this we conduct 20 interviews with domestic workers and household employers in Jordan, exploring privacy attitudes and practices. Our analysis uncovers a complex interplay between religious and social norms; legal and regulatory perspectives on privacy; and tensions between households and their domestic workers. We explore issues arising from smart homes coexisting as a residence and workplace, and highlight how workplace protections are ill-suited. We structure our findings to help inform public awareness, policy makers, manufacturers, and future research.