Responding to Deepfake Challenges in the United Kingdom: Legal and Technical Insights with Recommendations

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Cyberspace, Cyberterrorism and the International Security in the Fourth Industrial Revolution
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Abstract

The rapid progression of Deep Machine Learning (DML) and Artificial Intelligence (AI) technologies over the past decade has ushered in a new era of digital innovation. Alongside these developments emerges a complex landscape fraught with both technical and legal intricacies. This chapter delves into the multifaceted phenomenon of deepfakes, exploring the challenges they pose at the intersection of law and technology. To this end, the chapter examines the intricate interplay between legal and technical challenges inherent to deepfake technology. A particular focus is placed on the inherent biases within deepfake detectors, illuminating their implications. Furthermore, the evolution towards 3D-GAN (Three-Dimensional Generative Adversarial Network) technology is analysed, uncovering the potential challenges it might present. Within the context of the United Kingdom (UK), this chapter highlights the notable absence of comprehensive legislation specifically addressing deepfakes, with no imminent policy changes on the horizon. Furthermore, an in-depth analysis of the ethical and legal complexities surrounding deepfake pornography is undertaken. Additionally, the chapter delves into the far-reaching implications of disinformation and the exacerbating role that deepfake technology can play in amplifying its impact. The chapter concludes by advocating for a collaborative effort that combines legislative reforms and enhanced digital literacy to effectively mitigate the potential threats posed by deepfake technology.

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Montasari, R. (2024). Responding to Deepfake Challenges in the United Kingdom: Legal and Technical Insights with Recommendations. In: Cyberspace, Cyberterrorism and the International Security in the Fourth Industrial Revolution. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-031-50454-9_12

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  • DOI: https://doi.org/10.1007/978-3-031-50454-9_12

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