Even if state of the art AI can solve some problems as competently as a human, it may not have a broader context to judge the value of the solution, especially when handling new and unexpected situations. Humans leverage their awareness, but what about machines?
Given current technology, it should be possible to build a machine that contains a model of consciousness. That machine would attribute consciousness to itself and to the people it interacts with. Moreover, it would use that attribution to make predictions about human behaviour and to put input data in context. It is the ASTOUND objective to build a machine with such capabilities.
The ASTOUND project will provide an Integrative Approach For Awareness Engineering to establish consciousness in machines. To achieve this goal the project will focus on the following activities:
- Develop an AI architecture for Artificial Consciousness based on the Attention Schema Theory (AST). It is a novel approach to human and social cognition that reconciles several cognitive neuroscience theories of consciousness, stating that subjective awareness results from the construction of an internal model of the “state of attention”.
- Implement the developed architecture into a contextually-aware conversational agent. This is to verify the hypothesis that an artificial consciousness based on AST will unambiguously improve selection of appropriate language registry, adaptation to the interlocutor, and long term coherence.
ASTOUND proposes to build a plausible human-brain architecture for consciousness capable of demonstrating an undeniable added value in terms of human-machine interaction. This will be obtained by combining state of the art deep neural networks models with an Attention Schema.
The Attention Schema Theory (AST) , first conceived by Dr. Michael Graziano (Princeton Neuroscience Institute, part of ASTOUND’s team), explains the brain basis of subjective awareness in a mechanistic and scientifically testable manner. According to the AST, the brain is an information-processing device with the capacity to focus its processing resources more on some signals than on others.
The theory proposes that brains construct subjective awareness as a schematic model of the process of attention. Dr. Graziano’s team trained an artificial deep Q-learning neural network agent to control a simple form of visuospatial attention, tracking a stimulus with an attention spotlight to solve a catching task. The results show how the presence of even a simple attention schema can provide a profound benefit as a controller of attention. Dr. Graziano will collaborate to highlight the implications of the Attention Schema Theory on the generation and understanding of language, which are human specific abilities, which are related to consciousness in a more subtle, but maybe even deeper, way than visuospatial attention.
The final goal is to pose the basis for effective collaboration between humans and machines, promoting machines from the status of tools to those of (empathic) partners. ASTOUND, more specifically, aims at verifying the hypothesis that providing a virtual agent with artificial consciousness, in the sense of an attention schema, will unambiguously improve its performance in a task of natural language understanding. The innovative consciousness architecture based on the AST will be incorporated into a cross-domain, self-adaptive conversational agent. It will be designed to learn and adapt to new contexts and topics based on user interaction.
ASTOUND is expected to prove that the AST model has an impact on:
- Improved user engagement through the perceived quality of the service (socialcompetence of the chatbot).
- Achieving full personalization through user profiling and context-awareness mechanisms.
The first direct contribution of ASTOUND will be an engineering method for the realization of “conscious” conversational agents (Chatbots) able to deliver more human-like and natural communication. These agents will also be able to learn from their own mistakes, through self-assessment. We can expect to drive the European Chatbot market segment in multiple verticals, such as Healthcare, Education, BFSI (Banking, Financial Services, and Insurance), Retail and Ecommerce, Telecom, and Manufacturing.
The greater AI community will also benefit from the achievement of ASTOUND in terms of performance, robustness, trustworthiness, explicability (in the sense of reportability of internal states and the justifiability of decisions), and user experience.
Society has the potential to benefit from conscious AI, enabled by this project, at multiple levels.
- In the Transport sector, introducing advanced self-driven cars to reduce the rate of car accidents while decreasing urban traffic levels and consequently mobility greenhouse gas emissions.
- In the Healthcare Sector, providing human-like understanding and empathy to conversational agents could support mental health applications like personal AI therapists.
- Conscious conversational agents could potentially impact Education, allowing more effective e-learning tools for student assistance thanks to an extended coherence of which a conscious agent would be capable.
- In a completely different sector such as Cybersecurity, conscious virtual agents could support the interpretation of human motivations from vast realms of raw intelligence, which generally requires analyst oversight.
EIC PATHFINDER – FUNDED PROJECT
In 2022 Q1, the ASTOUND project was awarded a EIC Pathfinder grant, under the umbrella of the Horizon Europe programme. This prestigious European funding scheme is dedicated to helping researchers realise an ambitious vision for a new technology with potential to create new markets and/or to address global challenges.