Human Cognitive Agency
How can individuals maintain judgment, autonomy, and responsibility in AI-mediated environments?
Research areas include:
- Human-AI decision making
- Cognitive agency assessment
- Metacognitive development
- AI-assisted reasoning
Research
Foundations of Human-Centered Cognitive Infrastructure
AEGT's research agenda explores the foundations of human-centered cognitive infrastructure. Our work spans education, governance, cognition, knowledge systems, and human-AI collaboration.
Research Areas
AI Literacy Beyond Tool Use
How can AI literacy move beyond prompts and tools toward cognitive ownership and intellectual development?
Research areas include:
- AI literacy frameworks
- Educational implementation
- Teacher education
- Assessment and evaluation
Personal Cognitive Infrastructure
How can individuals build long-term cognitive systems that support memory, learning, expertise, and identity?
Research areas include:
- Personal knowledge systems
- Longitudinal memory architectures
- Human-AI cognitive environments
- Cognitive continuity
Executable Cognition
How can reasoning become inspectable, verifiable, and reusable?
Research areas include:
- Structured reasoning systems
- Executable prompts
- Reasoning verification
- Human-AI co-reasoning
Cognitive Governance
How can institutions govern AI systems that influence knowledge, education, and public understanding?
Research areas include:
- Educational governance
- Epistemic governance
- AI accountability
- Governance architecture
Foundational Frameworks
Our research is supported by three interconnected frameworks.
Open Cognitive Graphs
Semantic infrastructure for structured knowledge and reasoning.
Decentralized governance of AI knowledge authority, shifting the power to define valid knowledge from algorithm owners to professional communities.
Endogenous Cognitive Topology
Models for strengthening human judgment and cognitive agency.
A method for developing metacognitive judgment through structured training, enabling people to act as judges of AI rather than followers of it.
Metabolic Intelligence
Adaptive systems for continuous learning and collective intelligence.
A protocol model using a minimal common structure to enable communities to self-organize into collective intelligence and treat error as a resource for learning.
Publications
Our research programme is grounded in a formal theoretical foundation developed across a series of publications, including arXiv papers on domain-constrained reasoning, epistemic governance, and semantic knowledge systems.
Collaborate
AEGT welcomes collaboration with researchers, educators, institutions, and governance bodies. If your work aligns with these areas, we would be pleased to explore collaboration.