AUTOMATING GOVERNANCE, GOVERNING AUTOMATION OVERVIEW
This topic area focuses on how the state and state-like entities use data and AI to exercise power over people. Our goal is to identify the risks and opportunities associated with these practices—an exercise in legal and moral diagnosis—then to understand what we should be aiming at, and then to design sociotechnical systems that achieve these objectives. Within this thematic area, one stream of research focuses on the implications of AI for public law, the other focuses on the broader question of how data and AI lead us to rethink questions about the authority of states and state-like entities (such as digital intermediaries).
On public law, our work encompasses doctrinal investigations of just how principles of Australian public law constrain government use of algorithms, as well as surveys of the public use of algorithms in jurisdictions around the world. It also includes political philosophical work on the moral foundations of administrative law, and work drawing on both political philosophy and philosophy of science to understand why it is so important that those in power can explain the decisions that they have made, either to those directly affected, or to those on whose behalf they are acting. We have explored how to incorporate legally mandated indeterminacy in algorithmically delivered public policy, as well as the moral foundations of discretion in the exercise of power. On the design side, we have developed detailed theoretical work to improve the explainability of planning systems that use model-based diagnosis, as well as developing model law for the use of algorithms by governments.
The second stream of research zooms out from the focus on administrative law to consider other dimensions of the exercise of power by states and non-state entities using data and AI systems. It includes historical perspectives on how states have always constructed their authority through reliance on control over particular kinds of information, as well as on the role of predictive power and anticipatory governance in political theory—unifying the role of predictions in, for example, economic forecasting with the contemporary political pre-eminence of data science. It includes a rethinking of political philosophy through the lens of 'Automatic Authorities'—automated systems whose authority over us we have automatically accepted—which itself leads to new analyses of power and its justification. On the design side, we are working on criteria for the assessment of algorithmic tools designed to answer the most basic question of democratic politics: the boundary problem of redistricting.