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ANU Law student and Collegians, Andrew Ray (Class 2015) wins international prize for essay on machine learning

Posted 18 Oct, 2019

Andrew, the only student from an Australian university among the 25 winners selected worldwide, explored the use of machine learning for complex executive decision-making in his essay.

This article about Andrew Ray, Class of 2014, is reproduced from the News and Events page of the ANU website, with kind permission of the University.
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Andrew Ray, a fifth-year Bachelor of Laws (Hons)/Science student at The Australian National University (ANU), was recently honoured for his award-winning essay in the Law category of the 2019 Global Undergraduate Awards.

Andrew, the only student from an Australian university among the 25 winners selected worldwide, explored the use of machine learning for complex executive decision-making in his essay.

The competition attracted more than 3,400 submissions, which were judged by over 400 academics from a broad range of disciplines. Andrew will join other winners and highly commended entrants presenting at the 2019 Global Undergraduate Awards conference in November in Dublin, Ireland.

He was also part of the group of ANU Law students that won the 2019 Innovate Law hackathon. More details can be found here.

In this Q&A, Andrew shares what the award means to him and how his ANU studies have nurtured his interest in legal technology.

What does winning this award mean to you?
I have really enjoyed researching the intersection between law and technology and hope to continue this interest following my graduation. I believe that this award and being able to present my research in Dublin will allow me to continue to work in this space and connect me with other like-minded individuals from around the world.

What inspired you to explore implications of the future use of machine learning for complex executive decision-making for your essay?
Growing up in the “technology generation”, I witnessed firsthand the rapid expansion of technological capability and use. Combining this interest with my law studies I became interested in how technological advancement impacts the legal system, and what reforms are needed to keep pace with the rapid development of artificial intelligence (AI) and machine learning.

I was able to pursue this interest in Legislative Drafting and Technology (LAWS4251), where I focussed on the use of AI in executive decision-making – a logical focus given the University’s location near government and the strong public law interest I developed through studying Australian Public Law (LAWS1205),Administrative Law (LAWS2201) and Commonwealth Constitutional Law (LAWS2202).

How has your interest in this field been enriched through your ANU Law studies?
My Legislative Drafting and Technology lecturer, Sarah Paloni, was extremely supportive of my choice of topic and worked with me as I prepared the essay for submission to the competition. My interest in the intersection between law and technology has been developed more broadly through my Bachelor of Laws (Hons)/Science degree, particularly through the electives offered by the ANU College of Law.

I was able to further my interest in law and technology through studying Information Technology Law (LAWS4245), Intellectual Property (LAWS2222), and Legislative Drafting and Technology, as well as through extracurricular pursuits including the 2019 #InnovateLaw Hackathon.

What will be some of the key themes you hope to explore in your presentation?
My presentation will focus on the potential benefits of machine learning for executive decision-making – namely, the speed and consistency in automated decision-making – before assessing the potential harms if laws regulating this type of decision-making do not keep up with developing technology. It will conclude by making recommendations for future law reform, especially to the Freedom of Information Act and the judicial review process more broadly.

These changes would ensure that individuals are aware when a decision that affects them has been made by a computer program and would prevent a decision from being sent back to the same program if a successful judicial review action is brought.

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Andrew Ray

CLASS OF 2014

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