PhD Affiliates CTMF Admin PhD Affiliates CTMF Admin

Calliope Vakalopoulou

Calliope investigates the ethical implications of using generative AI chatbots in mental health contexts, focusing on how such technologies challenge traditional notions of care, autonomy, and emotional integrity in therapeutic relationships.

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Claudia Gonzรกlez-Mรกrquez

Claudia Gonzรกlez-Mรกrquez is a Teaching and Research Fellow in Artificial Intelligence, Data, and the Rule of Law. Claudia is Programme Staff on the interdisciplinary MSc in Data and Artificial Intelligence Ethics, and serves as course organiser for โ€˜Data and Artificial Intelligence Ethics, Law and Governanceโ€™.

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Ayรงa Atabey

Ayรงa is a PhD candidate at the University of Edinburgh. She conducts interdisciplinary research at the intersection of law and human-computer interaction and focuses on fairness and child-centred AI in education.

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Claire Barale

Claire's current research focuses on building AI data-driven tools able to effectively and ethically improve legal decision making in the context of refugee law. She is exploring the links between machine learning and other disciplines such as law and human rights processes, cognitive sciences, human-AI cooperation and ethics.

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John Zerilli

May 2023 - April 2025

Prior to his appointment as Senior Lecturer in Digital Law at Kingโ€™s College London and Program Director of Kingโ€™s online LLM in Digital Law, Dr John Zerilli was Chancellorโ€™s Fellow (Assistant Professor) in AI, Data, and the Rule of Law at the University of Edinburgh.

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Mike Gregory

Mike is a Postdoctoral Research Fellow in the project โ€œDemocracy, Rights and the Rule of Law in the Data-driven Societyโ€ where he applies insights from republican political theory to issues in AI involvement in governmental decision procedures. Mike recently received a PhD with distinction for his thesis โ€œThe Kantian Republicโ€ at the University of Groningen. 

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Sasha Lee Smit

Sashaโ€™s research explores the intersection between healthcare, ethics, identity politics, and technology, specifically in identifying and analysing the role that machine learning plays in epistemically just or unjust healthcare practices. 

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