Regulating artificial intelligence in digital media: governance, ethics, ownership, and democratic resilience (2023–2026 review)
This review synthesizes scholarship published between 2023 and 2026 examining the intersection of artificial intelligence regulation and digital media. Drawing on systematic reviews, policy analyses, and empirical studies, the article maps the evolving regulatory landscape addressing AI-driven disinformation, examines ethical challenges posed by generative AI in communication, analyzes ownership patterns and power concentration among technology firms, and considers implications for media representation and democratic resilience. The review identifies competing priorities between regulatory interventions, ethical frameworks, and market dynamics, highlighting the need for integrated approaches that address both technical and sociopolitical dimensions of AI governance. Key findings reveal divergent regulatory philosophies across jurisdictions, persistent challenges in balancing innovation with protection of democratic values, and emerging multistakeholder frameworks that may offer pathways toward more resilient information ecosystems.
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Regulating artificial intelligence in digital media: governance, ethics, ownership, and democratic resilience (2023–2026 review)
Semantic Scholar · 2026
Abstract
This review synthesizes scholarship published between 2023 and 2026 examining the intersection of artificial intelligence regulation and digital media. Drawing on systematic reviews, policy analyses, and empirical studies, the article maps the evolving regulatory landscape addressing AI-driven disinformation, examines ethical challenges posed by generative AI in communication, analyzes ownership patterns and power concentration among technology firms, and considers implications for media representation and democratic resilience. The review identifies competing priorities between regulatory interventions, ethical frameworks, and market dynamics, highlighting the need for integrated approaches that address both technical and sociopolitical dimensions of AI governance. Key findings reveal divergent regulatory philosophies across jurisdictions, persistent challenges in balancing innovation with protection of democratic values, and emerging multistakeholder frameworks that may offer pathways toward more resilient information ecosystems.