Beware! Your Favorite Books Are Being Trained to Create Deepfake Content

Once upon a time, a software engineer named John stumbled upon a website that promised to generate free Harry Potter audiobooks. Sceptical but intrigued, he downloaded the file and hit play. As he listened, he realized that the audiobook was not read by a human but by a machine that sounded almost like the real narrator.

John had stumbled upon a deepfake audio generated by a machine learning algorithm that was trained on J.K. Rowling's Harry Potter audiobooks. The website he found was just the tip of the iceberg. In recent years, it has become easier to create realistic deepfakes, and companies are tapping into the potential of deep learning algorithms to train on copyrighted books.

Real-life Examples:

One company that is using this technology is OpenAI, which is training its language model GPT-3 on copyrighted books. In their demo, they showed how they trained their model to generate coherent and contextually appropriate answers to questions by feeding it with thousands of copyrighted books.

Another example is an AI chatbot named Replika, which is trained on books like The Catcher in the Rye and The Great Gatsby. The chatbot can mimic the personality and conversation style of the characters in the books to create a more personalized experience for users.

Critique:

While using copyrighted books for training machine learning models might seem like a harmless practice, it raises questions about ownership and privacy rights. For instance, who owns the data generated by these models, and how is it being used? Moreover, with the rise of fake news and misinformation, deepfake content generated from copyrighted books could potentially be a major problem.

Conclusion:

In conclusion, while using copyrighted books for training machine learning models might seem like a fascinating practice with potential applications in various fields, it also raises important ethical concerns. As companies explore new ways of using these models, it's important for policymakers and society at large to think carefully about the implications they might have.

References and Further Readings:

1. https://www.openai.com/blog/dall-e-2/

2. https://www.theverge.com/2020/7/8/21316466/openai-language-ai-gpt-3-seven-gpt-2-improvement

3. https://replika.ai/blog/can-an-ai-chatbot-help-you-feel-less-lonely