Ethical and Legal Challenges in Generative AI: A Multidisciplinary Investigation

Abstract

Generative AI models, especially those based on large-scale neural networks, have ushered in transformative capabilities in content creation, automation, and interaction. However, the rapid development and deployment of these systems pose serious ethical and legal questions. In this paper, I explore these challenges from a human-centered and legal-compliance perspective. I delve into algorithmic bias, misinformation, copyright infringement, data privacy violations, and the growing necessity of global regulations. Using open-source datasets and recent case studies, I analyze the tangible societal impact of gen- erative AI and propose a framework to embed ethical and legal awareness into design pipelines. This paper aims to contribute both academically and practically to the safe advancement of this powerful technology.

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