Year: 2025
Type: article
Abstract: This paper examines the intersection of artificial intelligence and data privacy, analyzing how innovations such as generative AI, large language models, and deepfakes are challenging current privacy laws and compliance frameworks. Through a comparative study of the GDPR and CCPA, this paper assesses regulatory gaps, identifies risks such as data misuse and security breaches, and proposes practical solutions, including privacy-by-design and stronger governance protocols. It offers a forward-looking approach to fostering legal and ethical accountability in AI deployment.
Source: eYLS (Yale Law School)
Author: Arokun, Esther
Institution: Seattle University
Language: English
Subfield: Law
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6989981143
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