Data as Likeness

72 Pages Posted: 12 Sep 2022 Last revised: 14 Mar 2023

See all articles by Zahra Takhshid

Zahra Takhshid

University of Denver Sturm College of Law; Harvard University - Berkman Klein Center for Internet & Society

Date Written: September 5, 2022

Abstract

Artificial Intelligence (“AI”) and data collection practices pose an ongoing threat to consumers’ privacy. But plaintiffs have struggled to articulate privacy harms associated with data collection in a way that would give them standing to sue. This is particularly a pressing issue given the advances in generative AI and the unauthorize uses of individual’s personal and biometric data.

This Article revisits the seemingly forgotten privacy tort of appropriation of likeness and argues that when data is conceptualized as likeness, this tort offers a unique opportunity to protect against unauthorized collection and use of personal data. Grounding its argument in the historical evolution of the tort of appropriation, this Article contends that an individual’s personal data is an aspect of a person’s unique digital identity, most-used by third parties in a data-driven world that should be covered by this tort.

Conceptualizing unauthorized personal data collection in this manner underscores the evolving nature of the common law of torts in recognizing new form of harms. It offers a solution for the current gridlock on data protection measures and the unauthorize use of one’s data in generative AI emerging technologies such as deep voice. Recent Supreme Court decisions have insisted that privacy victims show some form of concrete harm to achieve constitutional standing. Likewise, employing the privacy tort of appropriation of likeness and recognizing the concept of digital persona allows plaintiffs to establish standing by identifying a close historical or common-law analogue for their asserted privacy injury. Lastly, similar to other privacy torts, this approach can survive First Amendment objections.

Keywords: digital persona, privacy torts, common law, private law, generative AI, deep voice, deep fake, voice cloning, OpenAI, data collection, PII, personal identifiable data, appropriation of lioness, right of publicity

Suggested Citation

Takhshid, Zahra, Data as Likeness (September 5, 2022). U Denver Legal Studies Research Paper No. 22-12, Georgetown Law Journal, Forthcoming, Available at SSRN: https://ssrn.com/abstract=4210660 or http://dx.doi.org/10.2139/ssrn.4210660

Zahra Takhshid (Contact Author)

University of Denver Sturm College of Law ( email )

2255 E. Evans Avenue
Denver, CO 80208
United States

Harvard University - Berkman Klein Center for Internet & Society ( email )

Harvard Law School
23 Everett, 2nd Floor
Cambridge, MA 02138
United States

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