8588 modules
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SUST6002 2025-26
AI for Sustainability Techniques and Research Methods
This module focuses on AI technologies and its applications within sustainability. The core aim is to develop a conceptual understanding of the research challenges for the SustAI CDT themes. This will help to build a common language among the cohort, enabling them to work more effectively together. The module draws heavily on research, case studies and tutorials delivered by academics as well as our partners in industry, government and the third sector. -
SUST6002 2026-27
AI for Sustainability Techniques and Research Methods
This module focuses on AI technologies and its applications within sustainability. The core aim is to develop a conceptual understanding of the research challenges for the SustAI CDT themes. This will help to build a common language among the cohort, enabling them to work more effectively together. The module draws heavily on research, case studies and tutorials delivered by academics as well as our partners in industry, government and the third sector. -
MANG2113 2027-28
AI in Business and Society – Ethics and Sustainability
This course focuses on the ethical integration and applications of Artificial Intelligence (AI) in business settings, with a specific emphasis on the challenges and opportunities related to algorithmic bias, inequalities, and diversity management as part of social sustainability. Taking a holistic approach to sustainability, students will explore the theoretical concepts and practical applications to understand how AI technologies can perpetuate or mitigate biases, create environmental issues and how this is all linked to economic sustainability. Based on a critical evaluation of case studies regarding AI-induced inequalities, students will learn how to develop strategies for managing diversity and apply ethical frameworks to AI development and implementation. -
SSPC6010 2025-26
AI in Justice Systems: Theory and Research
This thought-provoking course introduces students to the AI technologies, and more broadly, the algorithms currently informing criminal justice policy and practice in contemporary justice systems. Theory and research from the fields of criminology and sociology are used to explore the complex role of the technologies. Students are also introduced to digital research methods for researching criminological and sociological topics to influence criminal justice policy. Additionally, the module considers the methodological and ethical issues that arise when researching topics such as online radicalisation and victimisation, for criminal justice policy impact.
While the module focuses on England and Wales, in order to deepen students’ appreciation of the merits and demerits of AI technologies and algorithms more broadly, and perceive common problems inherent in the technologies, international comparisons are embedded throughout the module.
Participation in this module does not require prior knowledge of how algorithms are operationalised or their technical dimensions. The module focuses on criminological and sociological perspectives on their use and their broader social, political, and cultural implications. -
SSPC6010 2026-27
AI in Justice Systems: Theory and Research
This thought-provoking course introduces students to the AI technologies, and more broadly, the algorithms currently informing criminal justice policy and practice in contemporary justice systems. Theory and research from the fields of criminology and sociology are used to explore the complex role of the technologies. Students are also introduced to digital research methods for researching criminological and sociological topics to influence criminal justice policy. Additionally, the module considers the methodological and ethical issues that arise when researching topics such as online radicalisation and victimisation, for criminal justice policy impact.
While the module focuses on England and Wales, in order to deepen students’ appreciation of the merits and demerits of AI technologies and algorithms more broadly, and perceive common problems inherent in the technologies, international comparisons are embedded throughout the module.
Participation in this module does not require prior knowledge of how algorithms are operationalised or their technical dimensions. The module focuses on criminological and sociological perspectives on their use and their broader social, political, and cultural implications. -
SSPC6904 2025-26
AI in social problem analysis and policy formation
In this module you will explore the application of Artificial Intelligence (AI) in analysing social problems and formulating public policy responses. You will examine how AI technologies are reshaping our understanding of societal issues and influencing policy-making processes. The module is designed for postgraduate students from various disciplines, particularly those interested in public policy, social sciences, and the societal implications of AI. -
SSPC6904 2026-27
AI in social problem analysis and policy formation
In this module you will explore the application of Artificial Intelligence (AI) in analysing social problems and formulating public policy responses. You will examine how AI technologies are reshaping our understanding of societal issues and influencing policy-making processes. The module is designed for postgraduate students from various disciplines, particularly those interested in public policy, social sciences, and the societal implications of AI. -
DIGI2002 2027-28
AI Utopias and the Climate Crisis
Artificial intelligence requires access to data and computation. Both data and computational are material: they are produced by people, made possible by resource extraction, need power to survive, and both inhabit and resculpt the landscape. The use of AI, then, contributes to the climate crisis, but that role can be hard to see, hidden as it often is by a veneer of utopian hype that surrounds the information technology sector. Drawing on scholarship from digital media studies, environmental history, computer science, science and technology studies, climate science, and archival science, this module examines the past, present, and future intersections of AI, data, computation, and the natural environment. It lifts the lid on the countercultural origins of techno-utopianism. It examines the environmental degradation and injustices that techno-utopianism has and continues to hide (e.g. the instrumentalisation of personal climate responsibility). And it opens a pathway for building an intersectional and justice-oriented environmentalist practice in relation to AI. -
DIGI2002 2026-27
AI Utopias and the Climate Crisis
Artificial intelligence requires access to data and computation. Both data and computational are material: they are produced by people, made possible by resource extraction, need power to survive, and both inhabit and resculpt the landscape. The use of AI, then, contributes to the climate crisis, but that role can be hard to see, hidden as it often is by a veneer of utopian hype that surrounds the information technology sector. Drawing on scholarship from digital media studies, environmental history, computer science, science and technology studies, climate science, and archival science, this module examines the past, present, and future intersections of AI, data, computation, and the natural environment. It lifts the lid on the countercultural origins of techno-utopianism. It examines the environmental degradation and injustices that techno-utopianism has and continues to hide (e.g. the instrumentalisation of personal climate responsibility). And it opens a pathway for building an intersectional and justice-oriented environmentalist practice in relation to AI. -
DIGI2002 2028-29
AI Utopias and the Climate Crisis
Artificial intelligence requires access to data and computation. Both data and computational are material: they are produced by people, made possible by resource extraction, need power to survive, and both inhabit and resculpt the landscape. The use of AI, then, contributes to the climate crisis, but that role can be hard to see, hidden as it often is by a veneer of utopian hype that surrounds the information technology sector. Drawing on scholarship from digital media studies, environmental history, computer science, science and technology studies, climate science, and archival science, this module examines the past, present, and future intersections of AI, data, computation, and the natural environment. It lifts the lid on the countercultural origins of techno-utopianism. It examines the environmental degradation and injustices that techno-utopianism has and continues to hide (e.g. the instrumentalisation of personal climate responsibility). And it opens a pathway for building an intersectional and justice-oriented environmentalist practice in relation to AI.