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Explicit AI Deepfakes and Legal Challenges
Analytics Insight
|Crypto Scandals
Have you ever thought about the unsettling reality of deepfakes?
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Artificial intelligence has introduced massive challenges related to deepfakes. Deepfakes are hyper-realistic digital forgeries created using Al techniques, such as Generative Adversarial Networks (GANs). This manipulation can occur in images, videos, and audio, resulting in content that closely resembles reality but is entirely fabricated. While deepfakes hold potential for future applications in entertainment and educational media, they also raise difficult legal and ethical questions, especially when used to create explicit material.
The History of Deepfakes
Deepfake technology was discovered on the back of GANs, and the Al discovery by Ian Goodfellow and his team was introduced in 2014. GANs are a combination of two neural networks: the generator, which produces synthetic data, and the discriminator, which rates the authenticity of the data. As the iterations go on, the generator generates the output, making it impossible for the discriminator to classify whether it is actual data or just fake data. This ability led to the production of highly realistic deepfakes that can befool even the most discerning viewers.
Legal and Ethical Concerns
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