Improving social competences of virtual agents through artificial consciousness based on the Attention Schema Theory
ASTOUND aims to develop an AI architecture for artificial consciousness using Attention Schema Theory to enhance social interaction and natural language understanding in machines.
Projectdetails
Introduction
In the last decade, deep learning algorithms have enabled AI systems to perform a series of tasks, like speech and image recognition, as well as or better than humans. However, this technology is not going to be enough to deliver human-level intelligence without consciousness.
Importance of Consciousness
Without understanding the subjective awareness element, it may be impossible to build AI that has a human-like ability to focus its computational resources and intelligently control that focus and interact with people in a socially competent manner.
ASTOUND Proposal
ASTOUND proposes an Integrative Approach For Awareness Engineering to establish consciousness in machines. The approach consists of:
- An AI architecture for Artificial Consciousness based on the Attention Schema Theory (AST).
- A novel approach to social cognition that reconciles some of the current most debated cognitive neuroscience theories of consciousness.
Attention Schema Theory
According to the AST, the brain constructs subjective awareness as a schematic model of the process of attention. This suggests that an information-processing machine could attribute consciousness properties to others in a similar way.
Proposed Architecture
The AST-based architecture proposed by ASTOUND will combine:
- An Attention Mechanism provided by the attentional layers in a deep neural architecture.
- A Long Term Memory module allowing interplay between internal and external stimuli (data).
- An Attention Schema that will determine empathic and trustworthy decision-making.
Implementation
ASTOUND will first implement this architecture into a virtual conversational agent (i.e., chatbot) to verify the hypothesis that an artificial consciousness based on AST will improve performance in a task of natural language understanding.
Future Insights
ASTOUND will provide insights into consciousness that are concrete enough, and mechanistic enough, that engineers can build upon it to facilitate future technologies. The study has the potential to be a toolbox for the construction of an EIC Portfolio in conscious AI.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 3.330.897 |
Totale projectbegroting | € 3.330.897 |
Tijdlijn
Startdatum | 1-12-2022 |
Einddatum | 30-11-2025 |
Subsidiejaar | 2022 |
Partners & Locaties
Projectpartners
- UNIVERSIDAD POLITECNICA DE MADRIDpenvoerder
- INDEEP ARTIFICIAL INTELLIGENCE SL
- UNIVERSITAETSKLINIKUM HAMBURG-EPPENDORF
- ECOLE NORMALE SUPERIEURE
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Land(en)
Vergelijkbare projecten binnen EIC Pathfinder
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Counterfactual Assessment and Valuation for Awareness ArchitectureThe CAVAA project aims to develop a computational architecture for awareness in biological and technological systems, enhancing user experience through explainability and adaptability in various applications. | EIC Pathfinder | € 3.132.460 | 2022 | Details |
Context-aware adaptive visualizations for critical decision makingSYMBIOTIK aims to enhance decision-making in critical scenarios through an AI-driven, human-InfoVis interaction framework that fosters awareness and emotional intelligence. | EIC Pathfinder | € 4.485.655 | 2022 | Details |
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Value-Aware Artificial IntelligenceThe VALAWAI project aims to develop a toolbox for Value-Aware AI that integrates moral consciousness to enhance ethical decision-making in social media, robotics, and medical protocols. | EIC Pathfinder | € 3.926.432 | 2022 | Details |
Symbolic logic framework for situational awareness in mixed autonomySymAware aims to develop a comprehensive framework for situational awareness in multi-agent systems, enhancing collaboration and safety between autonomous agents and humans through advanced reasoning and risk assessment. | EIC Pathfinder | € 3.980.291 | 2022 | Details |
Counterfactual Assessment and Valuation for Awareness Architecture
The CAVAA project aims to develop a computational architecture for awareness in biological and technological systems, enhancing user experience through explainability and adaptability in various applications.
Context-aware adaptive visualizations for critical decision making
SYMBIOTIK aims to enhance decision-making in critical scenarios through an AI-driven, human-InfoVis interaction framework that fosters awareness and emotional intelligence.
Emergent awareness from minimal collectives
EMERGE aims to develop a framework for collaborative awareness in minimal artificial agents, enabling complex cooperative behaviors without shared language or pre-defined protocols.
Value-Aware Artificial Intelligence
The VALAWAI project aims to develop a toolbox for Value-Aware AI that integrates moral consciousness to enhance ethical decision-making in social media, robotics, and medical protocols.
Symbolic logic framework for situational awareness in mixed autonomy
SymAware aims to develop a comprehensive framework for situational awareness in multi-agent systems, enhancing collaboration and safety between autonomous agents and humans through advanced reasoning and risk assessment.
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Towards an Artificial Cognitive Science
This project aims to establish a new field of artificial cognitive science by applying cognitive psychology to enhance the learning and decision-making of advanced AI models.
The Global Latent Workspace: towards AI models of flexible cognition
This project aims to implement the Global Workspace Theory in deep learning to enhance AI's cognitive flexibility and robustness by integrating sensory and semantic information through neural translation.
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Dit project ontwikkelt een innovatief AI-platform dat gebruikers betrekt bij het verbeteren van algoritmen via feedbackloops, gericht op transparantie en betrouwbaarheid in de geestelijke gezondheidszorg.
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