Digital Media Concepts/AI Human Clones

Introduction

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Artificial intelligence (AI) technology can be engineered to digitally replicate the physical appearance and traits of human beings through advanced algorithms and computational techniques [1]. The concept of AI clones has sparked discussions about the boundaries of AI and the ethical implications of clones created by it.

Using techniques such as natural language processing, image processing with convolutional neural networks, and motion replication, AI clones emulate human characteristics. These clones have diverse applications, but also pose ethical challenges that call for legal responses.

 

Technical Aspects

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AI uses voice, physical appearance, and movements to create an identical 2D version of a human. Voice clones use natural language processing (NLP) and text to speech to understand the given text and convert it to speaking [2]. The process typically begins with the collection of vast amounts of data related to speaking conventions, accents, tones, etc. Some popular websites that offer AI voice cloning include Speechify, Eleven Labs, and Resemble AI. To match physical appearance, AI models intake data such as images of the individual being cloned.

These models then use convolutional neural networks (CNN) to process images and extract features [3]. After images have been processed, generative models like Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs) generate new images of human faces based on learned feature representations [4].

Finally, to replicate movements, cameras and motion sensors are used to record poses and movements by the clone subject. These movements will be processed and replicated by the AI model [5]. AI clones can incorporate reinforcement learning techniques to adapt and improve over time based on feedback and interaction with users, allowing them to refine their understanding and behavior. The mass amount of data and feedback are what help generative AI models improve their output.

Overall, the emulation of human characteristics by AI models requires a combination of advanced techniques in computer vision, natural language processing, machine learning, and human-computer interaction. By integrating these approaches, AI clones can effectively mimic human-like behaviors, emotions, and responses, creating more immersive and engaging interactions with users.

Benefits and Uses

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AI clones offer a wide range of practical applications that can significantly enhance productivity and streamline various tasks. By replicating human capabilities, these clones serve as valuable tools for efficiency. For instance, they can undertake responsibilities such as participating in meetings, handling phone calls, and producing videos [6].

AI clones can also play a crucial role in content creation. Beyond creating voice overs, these clones can emulate human characteristics and generate video content based on predetermined scripts. This content can then be posted across social media platforms or websites dedicated to content publishing [7]. While current AI cloning technologies aren’t seamless in replicating human actions, ongoing technological advancements and feedback integration hold the potential for significant improvements in the future. As these technologies continue to evolve, AI clones will become even more proficient and versatile, expanding their uses across various industries.

Challenges

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AI clones pose many ethical challenges. They can easily be used to impersonate public figures and personalities. In fact, there have already been scams using clones of celebrities like Taylor Swift, Oprah, and Dwayne "The Rock" Johnson to market certain products [8].

One significant concern is the lack of adequate legal frameworks addressing the identification and authentication of AI-generated content. Without robust laws regarding watermarking or other forms of identification, AI-generated content mimicking human behavior becomes indistinguishable from genuine human interaction [9]. This lack of distinction leaves the public vulnerable to exploitation, as unsuspecting individuals may fall victim to scams.

AI clones could also be used to deceive unsuspecting individuals. In the case of a company in Hong Kong, clones were used by scammers to trick a finance employee into paying $25 million from the company’s account. The unsuspecting employee had attended a Zoom call with AI clones of the CFO and other people at the company, asking him to transfer the money [10]. When placed in the wrong hands, AI clones cause ethical and practical concerns. Bad actors with malicious intent can exploit these technologies to manipulate and deceive. The proliferation of AI clones creates the need for careful consideration of the ethical implications and the regulations necessary to mitigate potential risks and protect against exploitation.

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While there aren’t extensive legal frameworks pertaining to AI cloning technology, there are a few that address potential challenges of these clones. In the US, the National Science and Technology Council’s Select Committee on Artificial Intelligence calls for improved methods of creating and monitoring AI through research, long-term investments, and collaboration [11].

Enforced by the European Union, the General Data Protection Regulation (GDPR) regulates the processing of personal data and grants individuals control over their data [12]. It applies to AI clones as they often handle personal information, helping ensure the responsible use of AI clones, and transparency in data processing.

The European Union also proposed the AI Act to regulate the development and use of artificial intelligence technology, including AI clones [13]. The act aims to ensure AI safety, transparency, accountability, and human oversight. These laws and regulations provide a legal framework for the ethical development and use of AI clones, protecting individual rights and privacy, as well as promoting responsible innovation and usage.

References

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  1. "Creating an AI Clone of Yourself: Bridging Fiction and Reality". ITRex. 2023-10-11. Retrieved 2024-03-24.
  2. "Creating an AI Clone of Yourself: Bridging Fiction and Reality". ITRex. 2023-10-11. Retrieved 2024-03-24.
  3. "What are Convolutional Neural Networks? | IBM". www.ibm.com. Retrieved 2024-03-24.
  4. Wenzel, Markus (2023). Colliot, Olivier. ed. Generative Adversarial Networks and Other Generative Models (in en). New York, NY: Springer US. pp. 139–192. doi:10.1007/978-1-0716-3195-9_5. ISBN 978-1-0716-3195-9. https://doi.org/10.1007/978-1-0716-3195-9_5. 
  5. "Creating an AI Clone of Yourself: Bridging Fiction and Reality". ITRex. 2023-10-11. Retrieved 2024-03-24.
  6. I Challenged My AI Clone to Replace Me for 24 Hours | WSJ, retrieved 2024-03-24
  7. I Challenged My AI Clone to Replace Me for 24 Hours | WSJ, retrieved 2024-03-24
  8. Herrman, John (2024-01-15). "Celebrities Already Live in AI Hell". Intelligencer. Retrieved 2024-03-24.
  9. "Generative AI Legal Issues". Deloitte United States. Retrieved 2024-03-24.
  10. Magramo, Heather Chen, Kathleen (2024-02-04). "Finance worker pays out $25 million after video call with deepfake 'chief financial officer'". CNN. Retrieved 2024-03-24.{{cite web}}: CS1 maint: multiple names: authors list (link)
  11. NATIONAL ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT STRATEGIC PLAN (PDF), May 2023, retrieved March 23, 2024
  12. "Data protection in the EU - European Commission". commission.europa.eu. 2023-07-04. Retrieved 2024-03-24.
  13. "AI Act | Shaping Europe's digital future". digital-strategy.ec.europa.eu. 2024-03-01. Retrieved 2024-03-24.