MARATTO

article · Archives of Current Research International

Deepfake Regulations and Their Impact on Content Creation in the Entertainment Industry

202411 citationsOpen accessUniversity of Ibadan

Abstract

This study investigates the impact of region-specific regulatory approaches on the use of deepfake technology within the entertainment industry, focusing on the United States, European Union, and China. Using data from the World Bank and OECD on regulatory quality and rule of law, the study employs a quantitative methodology that includes multivariate regression, chi-square tests, and logistic regression. Key findings reveal that while U.S. and EU regulations prioritize transparency and individual rights, China adopts a state-centered approach emphasizing social stability. Verification protocols in traditional media significantly enhance public trust (p < 0.001), while compliance costs support economic stability but slightly diminish trust. Social media platforms like YouTube and TikTok demonstrate robust content moderation policies, aligning more closely with regulatory expectations than Facebook and Twitter. The research highlights the influence of public opinion on regulatory effectiveness, noting its critical role in balancing innovation, ethical responsibility, and public trust. By examining the interplay of cultural, ethical, and economic factors, this study underscores the importance of harmonizing international regulations to mitigate the risks associated with deepfake technology. Recommendations include strengthening verification protocols, enhancing public digital literacy, and fostering global regulatory cooperation to create a framework that promotes innovation while safeguarding ethical standards. The findings offer valuable insights for policymakers, content creators, and media platforms navigating the complexities of AI-driven content in the digital age.

Research topics

  • Digital Media Forensic Detection
  • Generative Adversarial Networks and Image Synthesis

Sustainable Development Goals

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.9734/acri/2024/v24i12997

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.