The JUST AI Project
When:
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Venue:
Online
No booking required
The JUST AI project employs bibliometric methods and some social network analysis as part of a multi-method set of approaches that investigate the notion of networking and network-building in the emerging field and practice of data and AI ethics. The bibliometric and social network analysis portions of the project investigated how to map and understand who contributes to the field of data and AI ethics to identify its breadth and complexity and to investigate potential areas for further investigation using qualitative or design methods. Therefore, our use of these methods is descriptive and generative, acting as one kind of methodological investigation among others. Rather than being a mapping of a territory from outside, they are part of a broader conversation. In this talk we reflect on the choices made in this portion of the project and identify how these methods articulate with others.
Contact name:
BIDA
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Dr Alison Powell
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Dr Alison Powell is Associate Professor in Media and Communications at the London School of Economics. She directs the JUST AI Network: Joining Up Society and Technology for AI, which is supported by the AHRC and the Ada Lovelace Institute. Her research examines how people’s values influence the way technology is built, and how ethics in practice unfolds in technology design contexts. Alison’s work on open source projects, open hardware products and community-based innovation has spanned the past fifteen years and her book Undoing Optimization: Civic Action and Smart Cities is published by Yale University Press. This book identifies how citizens engage with the promise of smart cities, and suggests that integrated and systems-based thinking is required to enhance the ethical potential of civic action using technology. Her previous projects include the Horizon 2020-funded VIRT-EU, which examined ways to explore ethics in practice among Internet of Things developer communities and responsible innovation, and Understanding Automated Decisions, which considered the possibility and consequences of explaining how algorithms work. Alison undertakes collaborative, practice-based research through ‘data walking’ – see http://datawalking.com/.