Mark is a research-led academic with a pioneering cross-disciplinary vision that scans both the human and technical object in order to understand the societal dimensions of data, computation and AI. He has been PI or CI on EPSRC, H2020, and AHRC grants valued at more than £10 million. He collaborates with computer scientists in social data analytics and cybersecurity, social scientists and policy experts and legal scholars.

He is a PI and Strategic Board member of REPHRAIN, the UK's national research centre for online harm mitigation and data empowerment, and a PI on SoBigData, the European research infrastructure for social data analytics. He has collaborated with the Open Data Institute, British Library, the University of Pisa, Tactical Tech Collective and many others. He has presented his research at the British Academy, the European Parliament, the International Communication Association, the Royal Society, the Italian National Research Council, and many others.

His work has been published widely in leading journals across disciplines including Big Data & Society and the IEEE Computer. His innovative leadership in research-led teaching and curriculum development is demonstrated in the MA Data Culture and Society.

Research Interests and PhD Supervision

• Big Dat /Datafication
• Artificial Intelligence
• Cross-disciplinary research
• Media theory

Selected publications

• Seymour, W, Coté, M & Such, J 2022, Can you meaningfully consent in eight seconds? Identifying Ethical Issues with Verbal Consent for Voice Assistants. in Proceedings of the 4th Conference on Conversational User Interfaces. ACM. https://doi.org/10.1145/3543829.3544521
• van Nuenen, T., Such, J., & Coté, M. 2022. Intersectional Experiences of Unfair Treatment Caused by Automated Computational Systems. Proceedings of the ACM on Human-Computer Interaction - CSCW.
• Cote, M. and Pybus, J. 2017. Simondon on Datafication: A Techno-Cultural Method, Digital Culture and Society, 2(2), pp. 75-92.
• Pybus, J., Coté, M., Blanke, T. 2015. Hacking the social life of Big Data. Big Data & Society, 2(2), ISSN 2053-9517, pp. 1-10.

Teaching

Mark developed and leads the taught postgraduate programme MA in Big Data Culture and Society. He teaches modules that theorise data, artificial intelligence and machine learning with a focus on their social, political economic and philosophical dimensions. He also teaches a research-led module that introduces students to state-of-the-art practices in social data analytics, machine learning, and advanced explainability models for mobile apps and AI Assistants.

Expertise and Public Engagement

• Big DataArtificial Intelligence
• Cross-disciplinary research
• Data Privacy/Surveillance