The Law, Technology and Humans Journal has published the first machine-generated law review article.
Canadian law academics Benjamin Alarie (University of Toronto) and Arthur Cockfield (Queen’s University) approached the Journal’s Chief Editor Professor Kieran Tranter (Faculty of Business & Law) to have an AI software program known as GPT-3 write an article on a topic of his choosing. Supporting this proposal, Kieran suggested the following topic: “Why humans will always be better lawyers/drivers/CEOs/presidents/law professors than AI/Robots.”
The authors then put together some ‘seed text’ and the AI instantly produced the first machine-generated law review article, of sorts – the outcome provides a fascinating example of this application. While not a perfect example of a law journal article (without correct citations and peer review), the article demonstrates the potential for machine learning tools to process and create supporting texts that are both coherent and articulate. Professor Tranter says,
That GPT-3 wrote an article that was readable and sort of credible is a testament to the developments in deep learning and AI over the past 10 years. However, what is truly interesting about GPT-3’s text is what it reveals about us as humans. GPT-3 draws and synthesises from open access content on the internet. It is as if the digital archive of human life speaks back. What it says might surprise, dismay or delight.
The article has been made available ‘Online First’ and will also be published as a Feature in the next full issue in November (Volume 3, Issue 2 2021).
Law, Technology and Humans (ISSN 2652-4074) is an innovative open access, double blind reviewed journal that encourages research and scholarship on the human and humanity of law and technology. Supported by the Queensland University of Technology, Australia, Law, Technology and Humans is advised by a leading International Editorial Board.
For more information on Law, Technology and Humans, and to access published issues and articles, visit the Law Technology and Humans website.