The last edition of the IGDLCC podcast, realized by tech influencer George Buhnici and his team, focused on the sensitive topics of human trafficking and sexual exploitation. The podcast featured “Elena”, (the name was chosen at random to protect the identity of the real person) a victim exploited by a human trafficking ring, who managed to save herself from this terrible nightmare.
During the podcast, Elena’s identity was protected using the technology developed by Humans.ai, which leveraged complex AI to give her a new face and a new voice different from her real one while maintaining the emotional weight conveyed by a person who goes through such a traumatic experience.
Human trafficking is an abhorrent crime that sadly affects millions of people worldwide, preying on the vulnerable and causing immense suffering. One form of trafficking that has gained attention over the years is the “loverboy” method, where traffickers use romantic relationships to lure victims into exploitation. In the fight against this sinister practice, artificial intelligence emerges as a powerful ally that safeguards privacy and dignity.
Humans.ai has made a significant step in this direction by employing its AI technologies to protect the identity of Elena, a “loverboy” victim, preserving her privacy and supporting her on the path to recovery. To support victims and alleviate a fraction of their suffering, Humans.ai appeals to a series of innovative technologies to protect the identity of victims like Elena and guarantee anonymity. The AI Avatar technology developed by Humans.ai transposed a new face on Elena, able to accurately mimic facial expressions down to the level of micro expressions.
Elena’s story, along with many others like hers around the world, should never be minimized by a robotic voice. To ensure the emotional weight and feelings behind the words are preserved, Elena’s synthetic voice accurately replicates her emotions and voice inflections.
Humans.ai challenges the current perception of how video content is created by enabling a higher degree of freedom and flexibility when creating digital avatars. By leveraging complex artificial intelligence neural networks and blockchain, Humans.ai enables anyone, regardless of their tech prowess, to produce high-quality video content at scale without needing to hire real actors, a filming crew, or video editing professionals.
With its cutting-edge technologies, Humans.ai manage to create synthetic avatars with realistic lip synchronization and AI-generated voices, alongside other powerful AI models that facilitate content scraping and automatic language translation, which enables synthetic avatars to speak in any language of the world.
Advancements in artificial intelligence have ushered in a new era of technology, where the development of AI-generated synthetic voices become a common occurrence. These realistic and human-like voices are transforming how we interact with each other becoming a groundbreaking solution for preserving privacy and anonymity.
Humans.ai leverages Text-to-Speech technology (TTS), a branch of artificial intelligence that converts written text into natural-sounding speech. It allows computers and other devices to “read aloud” text-based content, providing a more interactive and accessible experience for users that preserves privacy.
The technology developed by Humans.ai generates a fully animated digital avatar with realistic lip synchronization for each language, making it a powerful tool that transcends language barriers that ensures anonymity.
Anonymization of Data: Ensure that all sensitive information such as names, addresses, and any other personally identifiable information (PII) is removed or obfuscated from the data before using it in AI algorithms.
Synthetic Data Generation: AI can be trained on synthetic data that retains emotional content without revealing specific personal details. Synthetic data is artificially generated and doesn’t contain any real information about the victims.
Differential Privacy: Implement differential privacy techniques to add noise to the data during training and inference, ensuring that individual records cannot be identified.
Federated Learning: Employ federated learning, where AI models are trained on decentralized devices without transmitting raw data, ensuring that sensitive information remains on the devices.
GANs for Emotion Preservation: Generative Adversarial Networks (GANs) can be used to create emotionally expressive content without relying on real data. This approach allows the model to understand and generate emotions without compromising the victim’s identity.
Contextual Understanding: AI models are trained to focus on understanding the emotional content without delving into personal details. Sentiment analysis and emotion recognition are utilized for this purpose.
User Consent and Control: Implement mechanisms to give users control over their data and emotions, allowing them to decide what information can be shared or used by AI systems.
Transparent and Explainable AI: Design AI models that can explain their decisions. This ensures that users and victims understand how their emotions are used without exposing their identity.
By combining these approaches, it is possible to use AI in a way that respects and protects the identity of victims while still preserving the emotional aspects of the data. It’s crucial to stay up-to-date with the latest advancements in privacy-preserving AI techniques to ensure the most effective protection for individuals.
The full podcast can be found below: