AI Safety and Fairness

The session will explore critical challenges in developing trustworthy AI systems, focusing on two interconnected domains: AI safety and fairness/bias mitigation. We’ll examine the fundamental problem of ensuring AI systems pursue intended objectives without causing unintended harm. The session will also address systemic bias in AI systems, exploring how training data, algorithmic design, and deployment contexts perpetuate social inequalities across domains like criminal justice, or healthcare.

Drawing on interdisciplinary research from computer science and social science, participants will analyse case studies, evaluate current technical approaches to these challenges, and critically assess the social and ethical implications of proposed solutions.

Outcomes:

Participants will:

• Identify key concepts and challenges related to AI safety and algorithmic fairness in contemporary AI systems;
• Analyse case studies to uncover how bias and safety risks emerge through training data, model design, and deployment contexts;
• Evaluate current technical and policy approaches to mitigating safety concerns and systemic bias in AI;
• Critically assess the social and ethical implications of deploying AI systems in domains such as healthcare, criminal justice, and education;
• Reflect on the role of interdisciplinary perspectives (from computer science and social sciences) in shaping more trustworthy and equitable AI systems.

Contributors:

• Maria Tzanou is Senior Lecturer in Law at the University of Sheffield and Director of the WRDTP’s Security, Conflict and Justice (SCJ) Pathway. Her research focuses on European constitutional and human rights law, privacy, data protection, surveillance, the regulation of new and emerging technologies and the inequalities of data privacy law and how these affect vulnerable groups.
• Marco Ortolani is Senior Lecturer in Responsible AI, Keele University formerly assistant professor at the University of Palermo (Italy) and visiting researcher on a Fulbright grant at the Missouri University of Science and Technology. Dr Ortolani specialises in responsible and human-centred AI, with a strong interest in medical applications. His current research interests focus on developing robust methods for aligning advanced AI systems with human values, combining rigorous theoretical alignment, oversight and control techniques, to help ensure AI remains safe, reliable and beneficial in high-stakes domains.
• Baidaa Al-Bander is a Lecturer in AI and Data Ethics, Keele University. Dr Al-Bander has experience in building explainable and fair AI systems for healthcare. Baidaa Al-Bander’s work has advanced AI techniques for retinal image analysis, particularly in DR, diabetic macular edema and glaucoma using CFP and OCT image. Her current work focuses on ensuring AI systems are ethical, fair, transparent and usable in real-world healthcare settings.

Important:

• This is an in-person event at The Wave, University of Sheffield (lunch and refreshments will be provided).
• You should bring your own laptop to this event.
• Spaces at this event are limited. We therefore ask that you only book a place if you are sure that you will be able to attend.
• Bookings will close at 9.00am on Wednesday 7th January.
• When booking, we ask that you use your institutional (.ac.uk) email address and complete all fields of the booking form. Thank you for your understanding.

Please note: The WRDTP is committed to sustainability and to reducing the waste from excess catering at events. A key challenge here is non-attendance at events. From October 1st 2025, the WRDTP will be changing the way we manage the non-attendance of PGR students who have booked place/s at WRDTP Training events. Any PGR student who does not inform the WRDTP (via training@wrdtp.ac.uk) that they will not be able to attend a WRDTP event at least 3 working days before the event takes place will have the cost of their place deducted from their RTSG (if a WRDTP-funded student), or have this charged to their department (if not funded by the WRDTP). This will allow us to better plan for events and to avoid catering waste. Thank you in advance for your cooperation on this matter.