Janina Boughey

When a government official tells you to do something, the instruction carries significantly more weight than when another person, without the cloak of government authority, issues the same instruction. If I tell a stranger not to smoke in a public place, they are very unlikely to stop smoking. For although I may be right about the harmful effects of their habit, I have no authority (at least in that context). But if the government puts up a ‘no smoking’ sign, or if a uniformed police officer, or, frankly, anyone in an official government uniform with perceived authority in the situation—such as a lifeguard on a beach or firefighter in the vicinity of a fire—tells a person to stop smoking, a fair number of people will obey. Certainly not all. But many, many more than if an ordinary member of the public issues the same command. This is so irrespective of whether the government official issuing the direction has actual legal authority to do so. Whether or not there is a law prohibiting smoking at that place, if the person issuing the order is perceived to have legal authority, then they are, in practice, exercising their special powers as a government official. And they ought to be treated as such and subject to public law accountability for the way they do so.

Yee-Fui Ng

I am deeply grateful to Frank Pasquale, Anna Huggins, and Alexandra Sinclair for their insightful comments on my book. It is such a pleasure to have such deep engagement and interaction with my work.

My decision to write this book stemmed from the large-scale scandals and controversies arising from automated decision-making that erupted in democracies such as Australia, the United States (US) and the United Kingdom (UK), which have harmed hundreds of thousands of people. The echoes of Robodebt in Australia, the MiDAS automated system in Michigan, and the UK Post Office Scandal reverberate until today, and prompted me to question: how did things go so wrong in these advanced liberal democracies with their sophisticated checks and balances?

Alexandra Sinclair

New technologies always lay bare the ambiguities present within existing frameworks of legal regulation. The use of artificial intelligence (AI) and automation in public-sector decision-making is no different. Automation in the administrative state has amplified the already contradictory and ambiguous aspects of administrative procedure. Does administrative decision-making necessitate a process of human cognition; are consultation obligations able to be met through AI simulation of public opinion; to what extent must courts exercise deference in evaluating the predictive assessments of AI models; and can the source code and training data of machine learning models satisfy the requirements of reason-giving are a few of the novel questions public sector automated decision-making raises.

Frank Pasquale

In her Combatting the Code: Regulating Automated Government Decision-Making in Comparative Context, Yee-Fui Ng examines many instances of predictive AI use that raise serious concerns about potential inaccuracy, discrimination, or alienation. Her penultimate chapter, ‘Towards a Framework for Technological Governance’, provides important methods for addressing these problems. The book also articulates normative foundations for a positive ideal of legal decision-making that is enhanced—not replaced by—AI.

This post, an appreciative response to the book, will focus on the reasons given for decisions, particularly given the rise of chatbots that can simulate reasoning processes. My main contention is that the principles animating Combatting the Code should not only lead us to demand reasons for automated decision-making, but in many cases should also require human reasoners to articulate such rationales in response to arguments posed by applicants and litigants.

Anna Huggins

Associate Professor Yee-Fui Ng’s new book, Combatting the Code, makes an important and timely contribution to debates about regulating automated government decision-making. Her in-depth comparative analysis of grounds of legal challenge for automated government decision-making across four dimensions (judicial review for rationality, anti-discrimination, public sector privacy and data protection, and freedom of information) in the United States (US), United Kingdom (UK), and Australia is an impressive feat. She also proposes a new framework for technological governance that moves beyond a focus on external legal and political accountability measures by foregrounding the importance of internal managerial controls for automated systems within government agencies.