The lab develops, disseminates and applies new sociotechnical research capabilities specific to Generative AI. Our research is in three key areas:
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Situating GenAI in the platform economy. The Lab undertakes continuous observation of the evolving GenAI economy and its integration with the digital communication technologies that are part of everyday life and work. Projects range from the role of GenAI in scholarly publishing to the emergence of authenticity infrastructure and the challenges of AI-generated content for media industries and the creator economy. In this work we address critical questions about power and agency with sociotechnical methods, including those that surface the experiences and voices of platform users and practitioners.
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Cultivating Responsible GenAI Systems. The Lab develops innovative approaches to ensure generative AI systems are responsive to diverse human values and social contexts. Projects range from creating advanced evaluation frameworks to pioneering interpretability techniques that enhance transparency and accountability. We investigate how these technologies can be modified and governed responsibly through cross-disciplinary collaboration, combining technical expertise with insights from media studies, science and technology, philosophy, law, and other disciplines. Our sociotechnical methods bridge computational approaches with human-centered perspectives, focusing on how GenAI systems can better respond to ethical considerations and community needs.
- Advancing public GenAI capabilities. The future of GenAI is not determined by the performance of models but also the skills of people using, deploying and implementing them. At the GenAI Lab we focus on re-imaging these human skills and machine capabilities together. We research new capabilities and explore innovative solutions to communicate them to the public through workshops, interactive tools, and critical explainers. We expect that as people are empowered in this way , they will come to see themselves as active participants in the development and implementation of AI models and recognise their role in shaping the future of generative technologies.