ÐÓ°ÉÂÛ̳ is supporting 16 new interdisciplinary AI focused research projects through its Research and Impact Support Fund (RISF). These projects, led by academic, research and policy staff and PhD students from across the School, will explore the impacts of AI on society, harness the power of AI to enhance research methodologies, and seek to refine and improve AI capabilities.
Professor Susana Mourato, Pro-Vice Chancellor: “At a time when AI profoundly impacts all aspects of life, there is an urgent need to better understand and guide AI’s development, adoption and deployment, and to harness its revolutionary capabilities to improve our understanding of the world. Social science research is essential to meeting this need. Through our internal seed funding, we are pleased to support projects which will help maximise the benefits of AI innovation in an equitable and ethical way.”
Below are details of the projects selected for the 2024 round of funding. Over the coming months we will share details of the research findings and related publications.
Funded projects and lead researchers
- Transformers for improved strategic learning
Galit Ashkenazi-Golan, Department of Mathematics
- Developing and testing a measure of responsivity to patient concerns
Alex Gillespie, Department of Psychological and Behavioural Science
- Practise what you preach: the relationship between AI narratives and actions in S&P 500 companies
Susanne Klausing, PhD Student, Department of Management
- Causal regressions controlling on images and text: theory on indentification and inference
Roberto Rafael Mauro, PhD Student, Department of Economics
- Humans behind the intelligent machine: AI, development and the future of work
Bingchun Meng, Department of Media and Communications
- Personal data stores for national statistics and evaluating socio-economic 'progress'
Georgia Meyer, PhD Student, Department of Management
- Occupational skill content and technological change
Thomas Monk, PhD Student, Centre for Economic Performance
- Generative AI and social scientific research Symposium
Thomas Robinson, Department of Methodology
- Data-driven streetscapes: decoding the social and political landscape of perceived neighbourhood context
Melissa Sands, Department of Government
- Machine learning for mental health: the use of reinforcement learning in an AI agent to improve depression
Sia Shahrizad, PhD Student, Department of Psychological and Behavioural Science
- Field experiments of social influence and contagion with AI-assisted bots
Milena Tsvetkova, Department of Methodology
- An Egalitarian Future of Work
, Centre for Philosophy of Natural and Social Sciences (CPNSS)
- Enhancing public deliberation with Generative AI: evidence from an AI-mediated conversational survey experiment
Chuyao Wang, PhD Student, Department of Methodology
- Graph Neural Networks with Application on Network Heterogeneity in Economics and Social Sciences
Yike Wang, Department of Economics
- The AI consciousness debate: ethical, conceptual and political implications
Jan Wasserziehr, PhD Student, Department of Government
- Transcending Privacy Barriers: the power of eco-positioning in enhancing AI acceptance
Ziqi Zhong, PhD Student, Department of Management