“Personality vs. Personalization” in AI Systems: An Introduction (Part 1)

In this piece authors Daniel Berrick & Stacey Gray (Future of Privacy Forum) look at how conversational AI technologies are increasingly shaping user experiences through hyper-personalization. From general purpose large language models to AI companions, corporate assistants, and educational aides, companies are racing to tailor interactions to individual preferences, behaviors, and contexts. This rapid evolution is driving new questions about how personal data is collected, stored, and inferred, and what risks emerge as these systems gain memory, broader access, and more distinct “personalities.”

The authors distinguish between two emerging trends: personalization and personality. Personalization adapts AI systems to a user’s history, preferences, or environment, raising concerns about privacy, transparency, and consent. Personality, on the other hand, refers to the increasingly human-like traits of these systems—such as humor, empathy, or skepticism—which can create new risks like manipulation, over-reliance, or emotional dependency. While the two concepts often overlap, analyzing them separately highlights how each interacts differently with existing US legal frameworks.

Ultimately, Berrick and Gray argue, these trends could have profound implications for both law and society. Personalization challenges existing data protection, consumer protection, and tort law, while personality tests the boundaries of social relationships and human-AI interactions. As these technologies advance, they are not only reshaping user experiences but also pushing lawmakers, regulators, and businesses to rethink how legal and ethical safeguards should evolve…

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