Wrong turns in Government by data and algorithm
Venue
Seminar Room 2, Chrystal Macmillan Building and on ZoomDescription
Part of the Controversies in the Data Society 2025 series
A cross-disciplinary series of public lectures and discussion on AI and the datafication of society
What directions are automated government taking in the 2020s? How and why are systems that attempt real-time identification and tracking of risky subjects seldom meeting our expectations of good government? The collection and use of information about citizens in order to plan and execute policy is one of the basic techniques of modern government. The use of surveillance, linked databases and rule-based algorithms is well established, and newer risk-based modelling is being trialled at scale. In these two talks, our speakers explore two different areas of government where this causes concern. Dr Gavin Sullivan explores global security infrastructures being put in place to support border security, and Dr Morgan Currie investigates attempts to introduce real-time welfare surveillance and payment in the UK.
Speakers
Dr Morgan Currie
Science, Technology and Innovation Studies
Morgan Currie is Senior Lecturer in Data and Society in Science, Technology and Innovation Studies (STIS) at the University of Edinburgh. Her research and teaching interests focus on open and administrative data, automation in the welfare state, and activists’ and everyday data practices. She co-organises the Critical Data Studies Cluster in the Edinburgh Futures Institute.
Selling Universal Credit: The Data Imaginary of Real Time Information
This talk examines the claims made by policy makers about a key technology underpinning the payment system of Universal Credit, the UK's largest social security payment: the Real Time Information (RTI) system. I draw on the theoretical framework of the data imaginary – how people mobilise the promises of data and algorithms to use technology in tactical ways fitting their goals and interests. Here, temporality is a particular facet of the data imaginary, as RTI promises to speed up the flow of data on work activity, creating a more responsive system for better decision-making. Lawmakers saw RTI as allowing them to assess claimant job outcomes, a key metric for measuring policy success, and as a new form of control by optimising people’s incentives to work and by mitigating error and fraud. We also find fragmenting opinions by MPs towards Universal Credit after the roll-out as constituents complain that RTI data is inaccurate and the Universal Credit system punitive. Even as Universal Credit is continually contested, policy makers successfully mobilise the RTI data imaginary to support their arguments for introducing Universal Credit.
- Recommended Reading
Podoletz, L., & Currie, M. (2024) Automating universal credit: A case of temporal governance. First Monday, 29(2). https://doi.org/10.5210/fm.v29i2.13580
Eubanks, V. (2018) The Digital Poorhouse. Harper’s Magazine. January. https://harpers.org/archive/2018/01/the-digital-poorhouse/
Dr Gavin Sullivan
Edinburgh Law School
Gavin Sullivan is a Reader in International Human Rights Law at Edinburgh Law School. He leads the UKRI Future Leaders Fellowship project, Infra-Legalities: Global Security Infrastructures, AI and International Law which examines how AI-security and automated decision-making is reshaping global security law and governance, focusing on the countering of terrorist and violent extremist content online and digital borders. He is a member of the International Advisory Committee of the Global Internet Forum to Counter Terrorism and Co-Director of the Scottish Council on Global Affairs.
UK Border Control and Algorithmic Risk Governance:
Mapping the Cerberus Digital Bordering Infrastructure
The 2025 UK Border Strategy seeks to ‘revolutionise’ UK border control through use of ‘advanced risk analytics’ and ‘AI-driven decision-making’. A key component of this regulatory shift is Cerberus – an advanced digital bordering system developed by the Home Office and British Aerospace Engineering that fuses diverse data for analysis by machine-learning algorithms to identify and preventatively govern ‘risky’ people and things. This presentation critically analyses Cerberus as a distinctive governance infrastructure, highlighting how it assembles risk and suspicion, and reconfigures both power and accountability in UK border governance and legal practices. It draws on a forthcoming paper in the German Law Journal (co-authored with Dimitri Van Den Meerssche) and interviews with Home Office experts and engineers designing this consequential AI-enabled security infrastructure.