Dr Yee-Fui Ng

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Contact details

Dr Yee-Fui Ng
Position/Fellowship type:
Visiting Research Fellow
Fellowship term:
28-Sep-2023 to 27-Nov-2023
Institute of Advanced Legal Studies
Home institution:
Monash University
Email address:

Research Summary and Profile

Research interests:
Project summary relevant to Fellowship:

Automation and comparative administrative law.

Vulnerable populations have been detrimentally affected by the Australian government’s use of

automated processes. In 2019, Professor Philip Alston, the United Nations Special Rapporteur on extreme

poverty and human rights, warned about the risks of the digital welfare state, where ‘digital data and

technologies … are used to automate, predict, identify, surveil, detect, target and punish’.1

The disastrous rollout of Robodebt, an automated system of calculating debts owed by social security

beneficiaries in Australia, is illustrative of the issues in automating government decision-making. Errors

of methodology of decision-making resulted in incorrect or inflated debt calculations for over 600,000

individuals. These large-scale incorrect calculations have reduced public trust in computer-supported

government decision-making and have led to grave repercussions for vulnerable low-socioeconomic

debtors. This includes indigenous people and individuals experiencing severe mental health issues, with

reports of suicide in the affected population.2

I am writing a book on automated government decision-making in the United Kingdom, United States and Australia, which is under contract with Cambridge University Press. I have conducted similar research in the United States on a Fulbright Scholarship, where I was hosted by Professor Philip Alston, the former UN Special Rapporteur on Extreme Poverty and Human Rights, and Chair of New York University’s Center for Human Rights and Global Justice. Aims This project aims to: · analyse the legal and political accountability frameworks that apply to automated decision-making systems in the UK, US, and Australia; · interrogate successful and suboptimal outcomes in government automation, and identify the factors that differentiate them; and · design best practice legal frameworks for government automation, supported by theoretical insights. The project will use analysis of successful strategies in the United Kingdom to identify optimal strategies for holding government accountable for its automated decision-making. Utilising these insights, the project will design a best practice legal framework for technological governance that protects the human rights of those affected.

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