The AMOR project explores user emotional and behavioral responses to news content displayed on a holographic wall (3D projected screen). News items are pre-analyzed for various attributes such as moral values, political bias, fake news indicators, and clickbait elements, then presented to user groups to study their reactions through AI-powered cameras.

Key Features:

• AI-driven analysis of news articles to extract multiple parameters including moral stances, political biases, fake news detection, and clickbait presence.
• Immersive presentation of news in virtual reality using a holographic projector.
• News narrated by a realistic 3D avatar powered by artificial intelligence, which interprets and vocalizes the news content to users.
• Real-time user interaction with the avatar via natural conversation enabled by an AI chatbot.
• Integration with large language models (LLMs) such as OpenAI’s API, with support for Azure services or local LLM execution.
• Text-to-Speech (TTS) and Speech-to-Text (STT) systems enable seamless voice communication between users and the AI avatar.
• Parametrizable AI behavior to adapt interaction dynamics.
• User reactions and interactions recorded by cameras and analyzed with AI to measure emotions and other response parameters.
• Pre-, during, and post-experiment questionnaires to gather comprehensive user feedback.
• The project aims to correlate user profiles with their emotional and behavioral responses to different types of news content, providing insights into how various audiences react to specific news attributes.

Developed for the Universidad Politécnica de Madrid

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Benefits and Impact

This project advances the understanding of how diverse audiences emotionally and cognitively engage with news content, especially in an era of increasing misinformation and polarized media. By combining immersive holographic technology with AI-driven interaction and emotion analysis, AMOR creates a novel, naturalistic setting to study real-time human responses. The insights gathered can benefit media literacy efforts, help design better fact-checking systems, and inform policymakers about the psychological impact of news framing and misinformation. Moreover, the use of advanced AI avatars fosters accessible, engaging interactions that could be extended to educational and therapeutic applications.

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Conclusion

The AMOR project demonstrates the potential of integrating AI, holography, and behavioral analysis to deepen our understanding of human-media interaction. It establishes a versatile platform for testing the emotional effects of news narratives and the effectiveness of AI-driven communication. The results highlight the value of multi-modal feedback—combining biometric, conversational, and questionnaire data—to build comprehensive user profiles and tailor information delivery. This multidisciplinary approach paves the way for future research on mitigating misinformation’s impact and enhancing user engagement with trustworthy news.