Building Trust and Social License in the UK: Driving a Sector Wide Ethical Shift in Public Engagement for Population and Administrative Data Research

Abstract

Use of population and administrative data has intensified ethical scrutiny around data security, representativeness, and research validity. Public trust has been weakened by data misuse, limited transparency, and poor alignment with community priorities. Existing engagement approaches are often inadequate for data-intensive environments where public roles and effective engagement remain poorly understood. In response, UK partners across disciplines and sectors established the Public Engagement in Data Research Initiative (PEDRI) and co-developed Good Practice Standards for Public Engagement in Data for Research and Statistics, alongside a public pledge. A PEDRI Frontiers meeting in June 2025 convened 60 stakeholders from government, regulation, industry, academia, community organisations, and the public. Participants compared the Standards with frameworks in their fields, examining their relevance to different publics and communities and highlighting strong alignment. Discussions focused on public engagement in statistics, administrative data, equity, diversity and inclusion, industry research, and artificial intelligence. This presentation will explore key insights, including evidence that involving the public as active partners in data use increases the relevance and impact of research while enabling communities to influence agendas and secure meaningful benefits. Definitions of “the public” vary across sectors and often require a broader, needs-based focus on what end users value. Participants mapped the Standards to existing frameworks in ethics, psychology, anthropology, political theory, and communication science. Cross-disciplinary mapping revealed trust as foundational, spanning transparency, accountability, and reciprocal benefit. The PEDRI Standards are enabling more democratic, effective, and socially accountable approaches to public engagement in data research.