Foundational Essays

Toward an Interaction-Centered Paradigm of Intelligence, Creativity, and Human–AI Co-Creation

-Nicholas Davis PhD

The essays authored by Nicholas Davis, PhD collected in this section represent the conceptual center of the Co-Creative AI research program. Together, they trace the development of an interaction-centered paradigm for artificial intelligence grounded in enactive cognition, participatory sense-making, computational creativity, adaptive systems, and human-centered AI.

Across more than a decade of interdisciplinary research, these works investigate a central question:

How do intelligence, creativity, and meaning emerge through interaction between humans, AI systems, and dynamic environments?

Rather than treating artificial intelligence as isolated computation or autonomous generation alone, these essays explore intelligence as an evolving process of participation, coordination, regulation, and adaptive sense-making unfolding across time. The research reframes co-creation not simply as shared artifact production, but as a dynamic process through which humans and intelligent systems construct meaning together through interaction itself.

A Research Lineage in Co-Creative AI

Many of the concepts explored throughout these essays emerged from early work in human–computer co-creativity and co-creative AI systems, including some of the earliest frameworks for: artistic computer colleagues, participatory sense-making in AI systems, quantified co-creation, creative trajectories, sense-making curves, interaction-centered AI, enactive models of creativity, and adaptive regulation under structural drift.

These ideas were operationalized through experimental systems such as: The Drawing Apprentice, AI Drawing Partner,  Aether, adaptive creative technologies, and enactive AI architectures. Together, these systems function as research platforms for studying how cognition, creativity, and collaboration emerge dynamically during human–AI interaction.

From Generation to Participation

A central theme connecting these essays is the distinction between generation and participation. Traditional AI paradigms often focus on prediction, optimization, classification, and autonomous output generation. In contrast, the work collected here investigates systems capable of sustaining meaningful interaction within evolving environments.

From this perspective: intelligence is relational rather than isolated, cognition emerges through interaction, creativity unfolds through participation, meaning evolves dynamically across time, and adaptive regulation becomes central to intelligent behavior. This interaction-centered perspective increasingly informs modern discussions surrounding: human-AI co-creation, hybrid intelligence, embodied AI, interactive machine learning, adaptive cognitive systems, explainable co-creative AI, and the future of human-centered artificial intelligence

Themes Across the Essays

Although each essay explores a different aspect of the broader framework, several recurring themes unify the collection.

Enaction and Sense-Making

Many of the essays draw from enactive cognitive science, which conceptualizes cognition as an active process of sense-making emerging through organism–environment interaction. These ideas provide a theoretical foundation for understanding co-creative AI systems as dynamically coupled participants rather than isolated generators.

Participatory Interaction

The work repeatedly examines how humans and AI systems coordinate actions, adapt to one another, negotiate meaning, and sustain collaboration across time. Interaction itself becomes a primary site of cognition and creativity.

Quantified Co-Creation

Several essays investigate how collaborative dynamics can be measured computationally through interaction traces, creative trajectories, and sense-making curves. These frameworks attempt to model the temporal structure of co-creation as it unfolds in real time.

Adaptive Regulation and Structural Drift

More recent work expands these ideas into broader adaptive systems research exploring how intelligent systems maintain coherent behavior under changing conditions. This includes research into structural drift, evolving environments, and interaction-centered regulatory architectures.

Interaction-Centered Intelligence

Collectively, these essays move toward a broader paradigm shift in artificial intelligence itself. Rather than understanding intelligence as static computation over fixed representations, this work explores intelligence as a dynamic process emerging through adaptive interaction between agents and environments.

Conceptual Foundations for Future AI Systems

The essays collected here are not intended merely as isolated theoretical reflections. They collectively form an evolving research program investigating how future AI systems may:

As artificial intelligence becomes increasingly integrated into creative work, communication, education, therapeutic systems, and everyday cognition, understanding interaction itself may become one of the defining challenges of next-generation AI research.

These foundational essays document one attempt to address that challenge through an interaction-centered approach to intelligence, creativity, and human–AI co-creation.