Abstract
We present here the first machine-generated law review article. Our self-interest motivates us to believe that knowledge workers who write complex articles drawing upon years of research and effort are safe from AI developments. However, how reasonable is it to persist in this belief given recent advances in AI research? With that topic in mind, we caused GPT-3, a state-of-the-art AI, to generate a paper that explains “why humans will always be better lawyers, drivers, CEOs, presidents, and law professors than artificial intelligence and robots can ever hope to be.” The resulting paper, with no edits apart from giving it a title and bolding the headings generated by GPT-3, is reproduced below. It is imperfect in a humorous way. Ironically, it is publishable “as-is” only because it is machine-generated. Nevertheless, the resulting paper is good enough to give us some pause for thought. Although GPT-3 is not up to the task of replacing law review authors currently, we are far less confident that GPT-5 or GPT-100 might not be up to the task in future.
Highlights
We present here the first machine-generated law review article
GPT-3 takes as input some user-provided text and outputs its own continuation of that text. Could such a machine author a law journal article? In the spirit of exploration, we proposed to Kieran Tranter, the general editor of this journal, to have GPT-3 write an article on a topic of his choosing
Before delving into the specifics of what makes humans so much more effective at certain tasks than machines or algorithms can ever hope to achieve, it helps to understand the difference between artificial intelligence (AI) and Machine learning (ML)
Summary
Will machines replace us? Over the last ten years or so, there has been a constant drumbeat warning us that robots will one day replace us. Kieran wrote back that he supported our proposed project and suggested the following topic: “Why humans will always be better lawyers/drivers/CEOs/presidents/law professors than AI/Robots.”. Because many kinds of studies within the humanities and social sciences cannot be replicated to provide verifiable lessons, it is difficult or impossible to evaluate whether they advance knowledge in any objective sense Scholars in these fields are, vulnerable to GPT-3 encroachments because the software is so effective at distilling large bodies of knowledge into coherent frameworks. For scholars who study non-scientific fields like law, GPT-3 ushers in a brave new world where machine-authored text will support us at first and later potentially replace us. It might be a good time for professors to check their pension benefits.
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