About | HeinOnline Law Journal Library | HeinOnline Law Journal Library | HeinOnline

LOG IN
LOG IN


19 Wash. J. L. Tech. & Arts 22 (2024)
When AI Remembers Too Much: Reinventing the Right to Be Forgotten for the Generative Age

handle is hein.journals/washjolta19 and id is 268 raw text is: WASHINGTON JOURNAL OF LAW, TECHNOLOGY & ARTS VOLUME 19, ISSUE 3 - SUMMER 2024 WHEN Al REMEMBERS TOO MUCH: REINVENTING THE RIGHT TO BE FORGOTTEN FOR THE GENERATIVE AGE Cheng-chi (Kirin) Changi ABSTRACT The emergence of generative artificial intelligence (AI) systems poses novel challenges for the right to be forgotten. While this right gained prominence following the 2014 Google Spain v. Gonzalez case, generative AI's limitless memory and ability to reproduce identifiable data from fragments threaten traditional conceptions of forgetting. This Article traces the evolution of the right to be forgotten from its privacy law origins towards an independent entitlement grounded in self-determination for personal information. However, it contends the inherent limitations of using current anonymization, deletion, and geographical blocking mechanisms to prevent Al models from retaining personal data render forgetting infeasible. Moreover, the technical costs of forgetting-including tracking derivations and retraining models-could undermine enforceability. Therefore, this article advocates for a balanced legal approach that acknowledges the value of the right to forget while considering the constraints of implementing the right for generative Al. Although existing frameworks like the European Union's GDPR provide a foundation, continuous regulatory evolution through oversight bodies and industry collaboration is imperative. This article underscores how the right to be forgotten must be reconceptualized to address the reality of generative Al systems. It provides an interdisciplinary analysis of this right's limitations and proposes strategies to reconcile human dignity and autonomy with the emerging technological realities of Al. This Article's original contribution lies in its nuanced approach to integrating legal and technical dimensions to develop adaptive frameworks for the right to be forgotten in the age of generative Al. 1 Incoming AI & The Future of Work Fellow, Emory University School of Law; Law Research Associate, Institute for Studies on AI and Law, Tsinghua University; JD, University of Florida Levin College of Law, 2024; LLM, University of Arizona James E. Rogers College of Law, 2022; LLB, National Chung Hsing University School of Law in Taiwan, 2021. I am thankful for the insightful feedback provided by Rachel Cohen, Youyang Zhong, Yilin (Jenny) Lu, Nanfeng Li, Edison Li, Shijie Xu, Yenpo Tseng, Chun-Ting Cho, Jeff Chang, Arron Fang, Ai-Jing Wu, Sabina Chen, Zih-Ting You, Li-Yin Hsiao, and Renee Wan, which enriched the content of this paper. Special thanks to Riri Wan for her thorough research support. I would like to further extend my appreciation to the editors of the Washington Journal of Law, Technology & Arts for their assistance in bringing this article to publication. Any errors or omissions are my sole responsibility. The views expressed in this article are solely my own and do not represent those of any affiliated institutions.