Deepfakes, leveraging artificial intelligence, have opened up possibilities for innovative applications in media, such as resurrecting deceased actors, restoring damaged footage, and enhancing live performances. However, these same techniques can be exploited for misuse, like spreading false news or disinformation, and infringing on privacy and consent rights. Our research methodology encompasses comprehensive examination of international regulatory frameworks, including the European Union's AI Act, China's deep synthesis regulations, and various national legislative initiatives implemented by different countries for regulating deep fakes. It also highlights improvements in laws and policies for controlling the misuse of AI in media. Despite the complex risks, the potential benefits of deepfakes, with thoughtful governance, may outweigh the drawbacks. AI governance in the media industry, especially for DeepFake usage, should align with industry standards and enforce stricter regulations to ensure proper oversight and accountability. This framework addresses key aspects such as consent requirements, transparency obligations, and compensation structures for affected parties. Despite the complex challenges posed by deepfakes, the paper argues that with thoughtful governance and appropriate safeguards, the potential benefits of this technology may outweigh its risks. The proposed regulatory approach aims to foster innovation while maintaining ethical standards and organizational integrity in the media and entertainment sectors. The research contributes significant empirical evidence supporting the necessity of balanced regulation while providing actionable recommendations for policy makers and industry practitioners. A proposed framework for Deepfake regulation in Media and Film Industry framework is proposed to regulate and legislate Deepfake usage in media and film industries, aiming to enhance control and organizational integrity.
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Hukam C. Yadav
Jay Oza
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Yadav et al. (Tue,) studied this question.
www.synapsesocial.com/papers/68d44c3431b076d99fa55374 — DOI: https://doi.org/10.36227/techrxiv.175744943.37338204/v1
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