Harry’s project investigates how moral expertise emerges through skilled engagement in relationships of reciprocal vulnerability and feedback, and how these mechanisms are disrupted in socio-technical systems that develop and deploy artificially intelligent systems.

Sasha’s research aims to explore how newly developed AI and machine learning (ML) tools may impact the epistemic climate that both healthcare users and professionals participate in. Her project aims to identify ways to create and implement measures to combat injustices without rejecting the benefits of ML in healthcare provision. 

Meenakshi’s work aims to explore explore how Indian EdTech engineers incorporate ideas about teaching and learning into the development of AI education technologies for K-12 classrooms. She aims to understand how ML infrastructures interact with and influence engineering practices in AI EdTech development.

Martin’s research project aims to develop and analyse a particular visual practice of artistic inquiry characterised by adversarial interventions with generative AI applications. This project offers a new perspective on the aesthetic, epistemic, evidential and translational value of art and design work that interrogates the ethical and cultural implications of generative AI.

Elisa’s work explores how we can empathise with the lived experience of ageing populations, designing digital devices and services that respond to their hopes and fears. The aim is to develop an expanded empathy framework for intergenerational inclusive design and codesign. 

Han-Ju’s PhD research focuses on the socio-ethical critique of technology adoption within Scottish social enterprises, stemming from her passion for investigating the intersection between the ethics of technology and alternative organisations.

Iñaki’s work investigates the role of dialogue design in shaping, discourse, normative content, and outcomes of public engagement with emerging technologies.

Yiping’s work focuses on the introduction of big data-driven technology — exploring the context, differences and process of the technology development, in addition to the performativity realized through stakeholders’ and partitioners’ engagement, discussion, cooperation and negotiation during the implementation process.

Charlotte's work will focus on AI ethics in creative spaces, such as the interdisciplinary discussions about computational creativity as a tool for enhancing AI ethics, generative models, and human-algorithm collaboration.

Andrew is interested in understanding the psychological and sociological effects technology has on moral reasoning and character and hopes to provide a framework to better understand these connections.

This project explores how AI can help "augment" human reasoning, using machine learning and natural language processing models.

This project incorporates a psychological perspective on AI ethics to inform the moral/ethical design of AI systems in the near future, paying special attention to human moral judgments and intuitions towards artificial agents.

This project explores the responsible usage of AI, in particular, learning to identify and mitigate bias and algorithmic (un)fairness. It looks to prevent the potential reinforcement and amplification of harmful existing human biases with applications to credit access and the financial industry.

This project explores the ethical and political implications of digitalisation and datafication in higher education. In particular, this research investigates the changing experiences and subjectivities of students in contemporary UK universities amid the growing importance of digital technologies, data and platforms.

This research develops a comprehensive responsibility framework to enable stakeholders involved in the design, development, and deployment of decision-making algorithms and autonomous systems to effectively govern and take responsibility for the outcomes of those systems in fields such as health, robotics, and finance

This project explores what the philosophy of science and in particular, the history and philosophy of measurement, can contribute to our understanding of the social and ethical implications of machine learning.

This research investigates models of collective data governance in agricultural ecosystems, evaluating them from a lens of power and inclusion, and their broader implications for responses to the climate crisis.

This project aims to synthesise philosophical bioethics and public deliberative processes, to arrive at recommendations for the ethical use of AI in healthcare resource allocation.