AI on the Frontlines: Towards a Theory of Administrative Fairness?


The ‘frontline’ of administrative decision-making is one of the primary domains of law and policy in action. But it is also more than that: it is a critical fairness interface in contemporary society with profound effects on the lives of individuals, as well as society, the economy, and the wider operation of government. Each year, there are billions of interactions between the state and members of the public around decision-making procedures in areas such as social security, community care, and immigration. How frontline decision-making operates is changing rapidly—not least because of the expanding use of digital technologies within government, including the use of AI and automated systems.

In this talk, we will explain how and why we are studying what constitutes “administrative fairness” in frontline state decision-making from the point of view of the public. We will set out our case that the public has sophisticated sensibilities about what constitutes fairness in administrative decision-making contexts and that these sensibilities are, in part, likely shaped by the use of AI and automation in such processes. We will also suggest that experiences of “administrative fairness” may shape the public’s behaviour in various other important ways (e.g their electoral participation). Finally, we will introduce how we are testing our nascent theory of “administrative fairness” through a range of empirical and experimental studies.