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77 Fla. L. Rev. 1 (2025)

handle is hein.journals/uflr77 and id is 1 raw text is: 






ARTIFICIAL   INTELLIGENCE AND PRIVACY


                      Daniel J. Solove*

                          Abstract
   This Article aims to establish a foundational understanding
of the intersection between  artificial intelligence (AI) and
privacy, outlining the current problems AI poses to privacy and
suggesting potential directions for the law's evolution in this
area. Thus far, few commentators  have  explored the overall
landscape of how AI and privacy interrelate. This Article seeks
to map that territory.
   Some   commentators   question whether   privacy  law  is
appropriate for addressing AL. In this Article, I contend that
although existing privacy law falls far short of resolving the
privacy problems with AI, privacy law properly conceptualized
and constituted would go a long way toward addressing them.
   Privacy problems  emerge  with  AI's inputs and  outputs.
These privacy problems are often not new; they are variations
of longstanding privacy  problems. But  AI remixes  existing
privacy problems in complex and unique ways. Some  problems
are blended together in ways that challenge existing regulatory
frameworks.  In  many   instances, AI  exacerbates  existing
problems, often threatening to take  them to unprecedented
levels.
   Overall, AI is not an unexpected upheaval for privacy; it is,
in many ways, the future that has long been predicted. But AI
glaringly exposes the longstanding shortcomings, infirmities,
and wrong  approaches of existing privacy laws.
   Ultimately, whether through patches to old laws or as part
of new laws, many  issues must be  addressed to confront the
privacy problems that AI is affecting. In this Article, I provide
a roadmap   to the key issues that the law must  tackle and
guidance about the approaches  that can work and  those that
will fail.


    * Eugene L. and Barbara A. Bernard Professor of Intellectual Property and
Technology Law, George Washington University Law School. Thanks to JP Schnabel
and Rose Patton for excellent research assistance. Thanks to Cathy Petrozzino for
useful feedback.

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