JOURNAL ARTICLE
THE IMPACT OF GENERATIVE AI ON PROTESTS: A NEW PARADIGM IN DIGITAL RESISTANCE.
Published In: Rutgers Computer & Technology Law Journal, 2024, v. 51, n. 1. P. 35 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Tanner, Susan 3 of 3
Abstract
In an era marked by rapid technological advancements and a surge in social activism, the intersection of privacy rights, misinformation, and libel laws has become increasingly complex and consequential. As protests and social movements increasingly rely on digital platforms to organize, communicate, and mobilize, they are also confronted with new challenges posed by the proliferation of artificial intelligence (AI) technologies. This article embarks on a timely and critical exploration of the ways in which AI is reshaping the landscape of privacy, misinformation, and libel in the context of protests, and proposes a comprehensive framework for safeguarding fundamental rights and fostering a more just and accountable digital future. The article begins by tracing the evolution of privacy rights in the United States, with a particular focus on the Fourth Amendment and the landmark case of Katz v. United States (1967). It examines how the rise of digital surveillance technologies, such as facial recognition and social media monitoring, has eroded privacy protections and chilled free speech and assembly, disproportionately impacting marginalized communities. Through a series of compelling case studies, including the surveillance of Black Lives Matter protesters in New York City and the use of Stingrays to track protesters in Miami, the article highlights the urgent need for stronger legal safeguards and oversight mechanisms. Next, the article examines the issue of misinformation in the digital age, exploring how AI-powered tools like deepfakes and synthetic media are blurring the lines between truth and falsehood, and undermining the credibility of protests and social movements. It analyzes the effectiveness and limitations of current regulatory approaches, such as Section 230 of the Communications Decency Act and the Digital Services Act in the European Union, and proposes a range of legal and technological solutions to combat the spread of misinformation while protecting free speech. The article then turns to the complex question of libel in the age of AI, examining how the rise of AI-generated content is challenging traditional notions of defamation and liability. Drawing on legal precedents such as New York Times Co. v. Sullivan (1964) and recent developments in jurisdictions like the United Kingdom, it explores potential reforms to libel laws, including adjusting standards of liability for AI-generated content, revising safe harbor provisions, and developing international legal frameworks. Ultimately, the article argues for a multi-stakeholder approach to navigating the challenges posed by AI in the context of protests and social movements. It calls for a combination of legal reforms, technological solutions, and public education efforts, grounded in a commitment to social justice and the centering of marginalized voices. It envisions a future in which the power of AI is harnessed to promote accountability, transparency, and the protection of fundamental rights, rather than being wielded as a tool of oppression and control. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Rutgers Computer & Technology Law Journal. 2024/07, Vol. 51, Issue 1, p35
- Document Type:Article
- Subject Area:Law
- Publication Date:2024
- ISSN:07358938
- Accession Number:184728024
- Copyright Statement:Copyright of Rutgers Computer & Technology Law Journal is the property of Rutgers Computer & Technology Law Journal and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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