Imagine a chatbot that doesn't just follow a script, but actually understands when to change its tone based on how you're feeling. It's like giving a computer a 'mental map' of attention so it knows what's important in a conversation. This helps the machine act more like an empathetic partner and less like a rigid tool.
Current AI lacks the subjective awareness to handle unexpected situations or adjust its social tone, making interactions feel robotic and lacking empathy.
An AI architecture based on Attention Schema Theory and a context-aware conversational agent. They also developed a 'Graziano/Turing test' to measure machine consciousness.
If you are a contact center provider dealing with frustrated customers who find bots robotic — this project developed a consciousness architecture that improves the selection of appropriate language and adaptation to the user. This makes interactions feel more natural and trustworthy.
If you are an app developer dealing with the need for empathetic digital support — this project developed a self-adaptive conversational agent. It uses an attention schema to provide empathic decision-making during user interactions.
If you are an EdTech company dealing with students who lose focus during AI tutoring — this project developed a system that attributes consciousness to the user to make predictions about behavior. This allows the agent to maintain long-term coherence in learning paths.
Based on available project data, no pricing or implementation costs are specified.
The project aims to provide a toolbox for the construction of an EIC Portfolio in conscious AI, suggesting a path toward scalable technology, though specific industrial scale metrics are not provided.
Based on available project data, specific licensing terms are not mentioned, but the project involves a consortium of 5 partners including one SME.
The architecture is designed to be incorporated into a cross-domain, self-adaptive conversational agent, combining deep neural architectures with a Long Term Memory module.
The project period is from 2022-12-01 to 2025-11-30, indicating the research and validation phase ends in late 2025.
The consortium is heavily research-oriented, consisting of 3 universities and 1 research organization, with only 1 SME (20% industry ratio). This suggests the output is currently a high-level scientific breakthrough rather than a commercial product, though the inclusion of an SME provides a bridge for future commercialization.
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