AI Fundamental Rights Impact Mining

The EU’s AI Act brings a range of A- based products into the scope of EU product regulation. It places a set of risk management and monitoring requirements that expand EU health and safety and consumer protection legislation by expanding the scope to protect Fundamental Rights [1]. A major challenge is the lack of an … Read more

Automated Regulatory Requirements Extraction – TAKEN

Organisations aiming to bring AI-based products onto the European Single Market must assess risks and compliance issues against a range of regulatory acts. While some legislation is supported by technical standards or codes of practice, organsiations increasingly have to track requirements from multiple  digital regulatory acts, e.g. the AI Act, GDPR, the Data Act, the … Read more

Research, Legislation and Standards Mapping Tool

Publicly funded research and innovation (R&I) projects and international standards development are two forms of collaborative technical activities that aim to provide benefits to markets and society, and yet coordination between them is often poor. Such coordination is complicated as both R&I projects and standards development projects both operate over fixed lifecycles, such that for … Read more

Regulatory Compliance of LLM Risk Assessments – TAKEN

The  EU AI Act calls for risk assessment to be conducted for AI systems in specific high risk applications and separately for systemic risks introduced by general-purpose AI (GPAI) systems (i.e. systems corresponding to the largest language models and their use as generative foundation models). The AI Act does not however provide guidance on how … Read more

Ethics Tracker for AI Research Projects – TAKEN

AI Researchers are increasingly called upon to anticipate and mitigate the harms arising from future use of their research, e.g. when publishing papers to major conferences [1][2][3] and journals or seeking funding from bodies like the EU [4]. The earlier the stage the AI research they work upon, the more challenging it is to imagine … Read more

[TAKEN] Intersectional Fairness in Machine Learning

This project focuses on the rich field of algorithmic fairness where the goal is to ensure that predictions are not biased against subgroups of the population whilst maximising predictive performance. One challenge is when we focus on multiple protected attributes.

Predicting Egocentric Visual Attention in 3D Action Contexts

Overview When people perform everyday actions, their eyes and attention don’t wander randomly; they shift in predictable ways depending on what the person is doing and where objects are in the environment. Understanding this link between actions, gaze, and 3D context is helpful for applications like VR/AR training, assistive systems, and human-robot collaboration. This project … Read more

[ALLOCATED] 25/26 PROJECT #5: Generative AI assisted synchronisation of knowledge graphs with evolving data source structures

Many knowledge graphs are not constructed from scratch, but rather are based on the ongoing uplift of data from existing data sources hosted in a variety of diverse data representations (relational data, JSON, CSV, XML etc.). The community has developed specifications that allow engineers who construct and maintain knowledge graphs to flexibly specify what data … Read more

[TAKEN] Investigating the Reproducibility of Studies which conducted Data Analysis or Machine Learning 

**This project is for students in the Statistics & Data Science programme (M.Sc) or MSc in Statistics and Sustainability ** “Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method. For the findings of a study to be reproducible means that results obtained by an experiment or an observational study … Read more