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Thinking With Machines
We are in the midst of a co-evolution - as we shift from occasional computer use in the 20th century to a merged co-intelligence in the 21st. This website explores this transition and its implications for learning, cognition, and human potential in the 21st century.
An Evolving Relationship
For most of computing history, our interactions with machines were discrete. Computers were tools to accomplish a task. Once complete, we disengaged.
Today, we're experiencing a fundamental shift toward persistent collaboration with intelligent systems that augment our cognitive capabilities in real-time.
IBM 360/85, 1971
This evolution blurs the traditional boundaries between human and machine intelligence, creating new cognitive ecosystems where knowledge is co-created rather than simply accessed. As AI systems become continuous partners in our thinking processes, we must reconsider what it means to learn, know, and create.
Central Research Questions

This project investigates how the transition from intermittent computer use to continuous AI partnership fundamentally reshapes human cognition, learning processes, and knowledge creation. We must understand this shift through multiple disciplinary lenses to harness its potential while addressing emerging challenges.
Meta-Learning & Future Skills
How we learn to learn with AI assistance
Distributed Cognition
How thinking extends beyond individual minds
Learning Science Fundamentals
How humans acquire and integrate knowledge
By creating this cross-disciplinary framework, we can better anticipate how co-intelligence will reshape education, expertise, and human potential in the coming decades.
Project Goals & Methodology
By mapping this rapidly evolving territory from multiple perspectives, we can anticipate transformative changes to education, knowledge work, and cognitive development.
Map the Conceptual Landscape
Integrate learning science, AI, cognitive psychology, and complex systems theory to create a cross-disciplinary framework.
Identify Key Transition Points
Document critical stages in human-computer interaction and learning that mark paradigm shifts.
Develop New Learning Models
Evolve learning theories for AI-augmented cognition and collaboration.
Anticipate Future Trajectories
Explore probable developments in co-intelligent systems and their implications for education.
Create Practical Applications
Translate insights into design principles for educational systems harnessing human-AI co-intelligence.
Why This Research Matters
We're at a turning point where learning is being reshaped. Our choices in designing and integrating AI will significantly impact human cognitive development and education for generations.
Redefining Expertise
With AI handling routine knowledge, human expertise shifts to creativity, contextual understanding, and complex problem-solving.
Transforming Education
Education must move beyond memorization to adaptive learning, critical thinking about AI content, and continuous skill development in human-AI collaboration.
Designing for Agency
We must design systems that enhance human agency, cognitive growth, and creativity, guided by learning science and ethical frameworks.
Learning science is key to understanding this transformation. Traditional theories must adapt to today's AI-augmented cognition.
Project Plan
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