Democratic Data Governance

Power differentials and participation in data governance (ESR11)

Governments and public bodies are increasingly using data-driven systems to automate decision-making processes for better policy decisions and better public service delivery. While there are some potential benefits of the application of AI in the public sector, there are several risks and challenges to do so effectively. These automated decisions can have severe impacts on individuals’ safety and welfare as well as damage communities and societies at a large scale. The governance of these technologies requires various public, private, and civil society actors to collaborate and for decision-making agency to be decentralised away from private organisations. There is a need for robust measures of governance, security, and accountability that put human agency and dignity at the centre.

This research aims to tackle this issue by investigating how participatory design can be used to envision democratic models of governance within data-driven systems. It aims to address power differentials and participation mechanisms to understand governance within a digital infrastructure.

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