About

Promoting Equity in Higher Education: A Socio-Technical Approach to AI Fairness

Our project is dedicated to advancing socio-technical approaches to fairness in Higher Education (HE) within the UK, with a specific focus on addressing bias and discrimination in AI-driven learning analytics systems. Institutions worldwide are recalibrating their data strategies for positive impacts on student success. However, the integration of fairness, both technically and socially, remains an understudied aspect of these strategies.

Leveraging the award-winning OUAnalyse (OUA) system at the Open University, our project seeks to establish a framework of best practices, risks, and compliance with UK regulations. This framework aims to guide HE institutions in the UK as they develop their digital strategies, emphasising the core principles of fairness and responsible AI.

The project will contribute to the broader discourse on ethical AI implementation in education, aligning with the UK government’s innovation-focused approach to AI regulation. Collaboration with regulatory bodies, such as The Equality & Human Rights Commission and The Information Commissioner’s Office, will ensure compliance of the provided framework with equality and human rights law, data protection, and sector-specific legislation.

This project has received funding from the UK Government - Department for Science, Innovation and Technology (DSIT). This funding is administered by UKRI.

News

Discover more about the latest developments, breakthroughs, and insights from our project. Our news section will serve as a dynamic hub, providing regular updates on our efforts to address bias and discrimination in learning analytics systems within Higher Education.

People

Team

Welcome from the team. We’re dedicated to tackling bias in UK Higher Education, ensuring a fair learning environment through innovative strategies and a responsible AI framework.

Professor Miriam Fernandez

As the Principal Investigator, she plays a key role in steering the project with her extensive expertise in Responsible Artificial Intelligence. Her aim is to ensure a cohesive integration of technical and ethical considerations, aligning with the project's socio-technical approach.

Dr Paul Mulholland

As Co-Investigator brings invaluable insights into Human-Computer Interaction (HCI) and user engagement. His expertise complements the technical knowledge of the team, enabling a holistic view of bias at both technical and social levels.

Vaclav Bayer

As the technical lead of the OU Analyse dashboard, Mr. Bayer's role is pivotal in overseeing all technical aspects, particularly in AI and predictive learning analytics. His expertise is foundational to the success of the project, ensuring robust technical developments and precise data analysis.

Dr Alba Morales Tirado

As the primary executor of project tasks, Dr. Tirado brings a wealth of knowledge in AI development and privacy. She will meticulously handle the technical, social, and policy aspects of addressing bias and fairness. Dr. Tirado's role is integral to the project's success, ensuring comprehensive coverage in creating a Responsible AI framework for Education.

See the Full Team