Data as Likeness
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 a particularly pressing issue given the advances in generative AI and the unauthorized uses of individuals’ personal and biometric data.
This Article revisits the privacy tort of appropriation of likeness and argues that when data are conceptualized as likeness, this tort offers a unique opportunity to protect against the 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 are an aspect of a person’s unique digital identity, mostly used by third parties in a data-driven world, which 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 forms of harms. It offers a solution for the current gridlock on data protection measures and the unauthorized use of one’s data in emerging generative AI technologies such as deep voice. Recent Supreme Court decisions have insisted that privacy victims must show some form of concrete harm to achieve constitutional standing. Accordingly, employing the privacy tort of appropriation of likeness and recognizing the concept of digital persona allow 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.
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