Generative AI in the Justice System: Legal Frameworks Present New Challenges
Article researched and reported by Sophia Kurz, written by ChatGPT and edited by Sophia Kurz and Gracie Warhurst.
Image created by openart.ai with the prompt: “AI in the justice system”
As the dawn of artificial intelligence (AI) continues to intersect with the legal profession, experts like Paul Watler, a partner at the law firm Jackson Walker LLP, and David Ryfe, a journalism professor and media director in the School of Journalism at the University of Texas, weigh in on the potential implications and challenges that AI might bring to the justice system.
One area where AI-generated content has already raised legal questions is copyright law. Watler explains that generative AI systems often scrape information from copyrighted material, such as books or opinion columns, leading to potential infringement issues. The concept of fair use, however, might protect some AI-generated content if it is used for scientific, academic or news reporting purposes.
AI-generated content has also sparked concerns about defamation. Watler mentions cases in which AI-generated reports falsely accused individuals of misconduct or harassment, resulting in legal disputes.
“There's an example of a law professor at George Washington University where a colleague forwarded him a generative AI paper that was talking about prominent law professors who had been accused of sexual harassment, and his name was listed in this report, when in fact, he had never been accused of sexual harassment,” Watler said.
According to Watler, while it is doubtful that a generative AI system could be held responsible, the journalists, news organizations or individuals who post content derived from AI-generated sources may be held accountable for that content.
Generative AI systems are not the only algorithms impacting the legal system. Ryfe points out that many police departments already use algorithms to predict criminal behavior, but these algorithms can produce biased outputs based on biased inputs. Algorithms are also used to record images and identify crime suspects, sometimes leading to false arrests and costly legal fees.
“It's been shown that there are significant biases in the algorithms, particularly,” Ryfe said. “It's kind of sampling bias because the algorithms are basically only as good as the inputs. And if the inputs are biased, then you're going to get outputs that are biased, and that's already happening in the legal community.”
As AI-driven systems become more prevalent, Ryfe emphasizes the need for guidance and oversight from the legal community to ensure that these tools are incorporated into the law and the courtroom in a responsible manner. This process will undoubtedly be bumpy and may result in real harm to individuals, but as the technology improves, so too will its integration into the legal system.
The future of generative AI in the justice system remains uncertain and Watler and Ryfe's insights demonstrate the unique challenges that AI technology presents.
Here is the prompt used for this article:
Write a journalism article about generative AI in the justice system and legal frameworks and incorporate quotes from the following transcriptions from BOTH sources, please: (transcriptions of interviews from Ryfe and Watler)