01
Interaction is constitutive
Interaction does not merely transmit information between pre-existing systems. It can transform the organization and capacities of the participants themselves.
An emerging scientific paradigm
The science of organization through interaction.
Interaction Science studies how cognition, intelligence, creativity, learning, identity, and collective organization emerge through interaction over time.
The field
What is Interaction Science?
Interaction Science is the systematic study of how coherent organization emerges, changes, and persists through interaction.
Many sciences begin with entities: particles, organisms, minds, agents, models, institutions. Interaction Science begins with what happens among them. It treats interaction not as background context, but as a primary site where cognition, intelligence, creativity, learning, and social organization are enacted.
The field asks how systems coordinate, how trajectories form, how regimes stabilize, how drift accumulates, how breakdown is repaired, and how new forms of order become possible. Its central objects are temporal: events, trajectories, attractors, regimes, transitions, coherence, drift, and regulation.
Interaction Science is not confined to one discipline. It provides a shared framework for inquiry across cognitive science, artificial intelligence, psychology, biology, education, design, therapy, organizational studies, and complex systems research.
Instead ofIsolated agents
StudyCoupled systems
ExplainOrganization over time
Manifesto and vision
Core principles
A concise statement of the commitments that distinguish Interaction Science as a field.
02
Time is explanatory
Order, meaning, and identity cannot be understood from snapshots alone. Their explanation lies in trajectories, histories, transitions, and timing.
03
Organization is relational
Coherence is often distributed across agents, tools, environments, practices, materials, and institutions rather than contained in one location.
04
Regulation complements prediction
Science must explain how systems respond when organization is threatened, disrupted, or opened to transformation.
05
Measurement should preserve process
Methods should capture interaction as it unfolds rather than reduce it prematurely to final outcomes or aggregate scores.
06
Multiple scales matter
Local events, regional regimes, and global developmental trends constrain and enable one another across time.
Canonical terminology
A shared vocabulary for temporal interaction
Select a concept to view its working definition.
Events
Meaningful changes in interaction.
Trajectories
Ordered paths through interaction states.
Attractors
Recurrent patterns of organization.
Regimes
Stable modes of interaction.
Drift
Accumulating movement and divergence.
Coherence
Organizational fit across time.
Regulation
Maintaining and reorganizing viability.
Transitions
Qualitative changes in organization.
Event
A bounded occurrence that changes the state, direction, or organization of an interaction. Events may be behavioral, perceptual, material, computational, or relational.
Educational resources
A reading roadmap into the field
Begin with the paradigm, then move toward temporal method, measurement, and application.
Stage 1 · Orient
Why interaction?
Understand the limits of isolated-agent and static-state explanations.
Stage 2 · Learn
Temporal foundations
Study events, trajectories, regimes, attractors, drift, and transitions.
Stage 3 · Measure
Interaction methods
Explore segmentation, modeling, visualization, interpretation, and multiscale analysis.
Stage 4 · Apply
Domains of practice
Connect the framework to AI, creativity, education, therapy, development, and organizations.
Why Interaction Science now?
Why has this field emerged in the 2020s rather than decades earlier?
Longstanding relational ideas are converging with new technical capacities and new scientific limitations.
Interaction has always mattered. What is new is our ability—and our need—to study it as a continuous, measurable, multiscale process.
AI has become interactiveArtificial intelligence increasingly participates in sustained collaboration, adaptation, and joint activity rather than producing isolated outputs.
Continuous behavioral data is abundantDigital systems now preserve sequences of action, response, revision, timing, and coordination at unprecedented scale.
Real-time sensing enables temporal measurementWearables, motion tracking, biosignals, multimodal interfaces, and environmental sensors reveal interaction as it unfolds.
Static benchmarks are reaching explanatory limitsOutcome scores can compare performance, but they often cannot explain development, repair, regulation, or reorganization.
Multiple disciplines are convergingCognitive science, HCI, AI, biology, education, therapy, and complex systems increasingly treat interaction as central to organization.
Temporal methods are becoming practicalTrajectory modeling, sequence analysis, dynamical systems, event segmentation, and interpretable visualization can now support a shared methodological program.
Foundational work
Papers, books, and intellectual lineages
A growing archive of scholarship that defines, supports, challenges, and extends the field.
Paradigm
Interaction Science: A Temporal Science of Cognition, Creativity, and Artificial Intelligence
Nicholas Davis · Foundational book project
FrameworkInteraction-Centered Intelligence: Toward an Interaction-Based Theory of Human–AI Co-Creation
Interaction-centered foundations for intelligence and collaboration.
Read PDF · arXiv 2606.00807 → MethodCognitive Trajectory Modeling: Quantifying Human–AI Co-Creation through Cognitively Grounded Interaction Trajectories
A method for analyzing cognition and co-creation through temporally ordered interaction trajectories.
Read PDF · arXiv 2606.15358 → Research lineageEnactive cognition, participatory sense-making, ecological psychology, dynamical systems, and interaction analysis
Related traditions that contribute to the emerging field
Research agenda
Open questions
Interaction Science is defined not only by what it claims, but by the problems it makes newly visible.
What are the natural units of interaction?
How should events, episodes, chapters, and regimes be segmented without destroying the continuity of process?
How can trajectories be compared?
Which measures preserve meaningful differences in timing, sequence, revisitation, curvature, and transition structure?
How does regulation operate across scales?
How do local adjustments reshape regional regimes and long-term developmental trajectories?
When does interaction become constitutive?
What evidence distinguishes interaction that merely influences a system from interaction that changes what the system is?
How should interaction-centered AI be evaluated?
What replaces isolated benchmark performance when intelligence is distributed across sustained human–AI participation?
What ethical responsibilities follow?
How should agency, authorship, accountability, power, and care be understood in relationally constituted systems?
History of the field
From relational traditions to a shared scientific program
Interaction Science does not appear from nowhere. It consolidates more than a century of work on relation, embodiment, feedback, coordination, dynamics, and distributed organization.
Phase I · Late 1800s–1970s
Foundations of Relational Thinking
Scientists and philosophers gradually recognized that many phenomena cannot be understood by examining isolated components alone. A set of overlapping traditions began to emphasize relation, organization, feedback, environment, and adaptation.
- Pragmatism
- Phenomenology
- Systems Theory
- Cybernetics
- Ecological Psychology
- General Systems Theory
Phase II · 1980s–2005
Cognition Becomes Embodied
A second wave shifted cognitive science away from explanations centered exclusively on internal computation. Cognition was increasingly understood as embodied, situated, distributed, and dynamically coupled to the world.
- Embodied cognition
- Enactive cognition
- Distributed cognition
- Dynamical systems
- Situated cognition
Cognition depends upon interaction with the world.
Phase III · 2005–2025
Interaction Becomes Constitutive
Researchers increasingly argued that interaction does not merely influence cognition from the outside. Interaction can participate in creating cognitive organization, shared meaning, agency, and new forms of coordinated activity.
- Participatory sense-making
- Human–AI co-creation
- Interaction analysis
- Creativity support tools
- Human–robot interaction
- Collaborative AI
Interaction does not only connect cognitive systems. It can help constitute them.
Despite this convergence, there was still no unified science devoted specifically to interaction itself as a primary and cross-domain object of inquiry.
Phase IV · 2026–
Interaction Science
Interaction Science proposes interaction itself as the primary object of scientific investigation. Rather than borrowing disconnected methods from psychology, AI, sociology, HCI, biology, or education, it seeks a common language for studying organization across domains.
- Interaction events
- Interaction trajectories
- Attractors
- Regimes
- Coherence
- Drift
- Regulation
- Emergence
The aim is a general science of how organization emerges, changes, persists, and reorganizes through interaction over time.
Timeline of Major Developments
Pragmatism
Cybernetics
General Systems Theory
Ecological Psychology
Distributed Cognition
The Embodied Mind
Mind in Life
Participatory Sense-Making
Human–AI Co-Creation
Interaction-Centered Intelligence
Cognitive Trajectory Modeling
Interaction Science
Community
A field becomes real when others can enter it.
This site is envisioned as a growing commons for researchers, practitioners, students, and institutions developing interaction-centered theories, methods, datasets, instruments, and applications.