73 Am. U. L. Rev. 1535 (2024).

Download PDF Here!

Abstract

Artificial intelligence is inescapable. It is in our phones, fridges, and most of the businesses we engage with use it to “improve” their services. From deciding on what YouTube video to watch next to driving vehicles or firing weapons, artificial intelligence is a linchpin in our society. But what is artificial intelligence? And, more importantly, why does that matter? It matters because we are currently unprepared to deal with the paradigm-shifting legal issues brought about by artificial intelligence. And without this understanding, we are nearly certainly going to make mistakes. The bright side is that artificial intelligence is not complicated. Artificial intelligence—more accurately, machine learning—is built on simple and intuitive concepts revolving around: (1) a particular type of machine known as a neural network; and (2) getting that machine to learn through a process of, or similar to, gradient descent. The aim of this Essay is to provide a low-level, accurate, and easy-to-digest explanation of what artificial intelligence is, providing a novel metaphor to aid in that explanation. Like a perpetual stew, models built with artificial intelligence start with a recipe (neural network architecture), are tweaked to a particular palate (training), and are set to live forever as long as they continue to produce tasty (accurate) results. In turn, the Essay provides the legal community with an accurate vantage point from which to analyze the many artificial-intelligence-based issues that will not be on the horizon for much longer.

* Ph.D. Candidate, University of Maryland, Department of Computer Science; M.S., Columbia University, Department of Computer Science; J.D., magna cum laude, Michigan State University College of Law.