Creative Sense-Making (CSM) is a framework develop by Nicholas Davis, PhD and colleagues for understanding creativity as an interactive process of meaning construction between agents, environments, and evolving constraints. Rather than treating creativity as the isolated production of novel artifacts within an individual mind, Creative Sense-Making views creativity as a dynamic process of participation, interpretation, adaptation, and co-regulation unfolding across interaction.
The framework emerged through research into co-creative systems, human-AI collaboration, improvisational interaction, and enactive cognition. It was developed by Nicholas Davis during doctoral research in Human-Centered Computing at the Georgia Institute of Technology, where the focus shifted from evaluating creative products alone toward examining the interaction dynamics that give rise to creativity in the first place.
At the center of Creative Sense-Making is a simple but powerful observation:
Creativity does not emerge solely from internal thought. It emerges through interaction with a changing world.
This interaction may occur between: a human and an AI system, two collaborators, an artist and their materials, a musician and an audience, or an individual and the unfolding affordances of an environment. In all cases, creativity is not merely generated internally and then expressed outward. Instead, meaning and possibility emerge through recursive engagement.
Traditional models of creativity often focus on: idea generation, divergent thinking, problem solving, or evaluation of finished artifacts. While useful, these approaches frequently isolate creativity inside the individual mind. Creative Sense-Making instead proposes that creativity is fundamentally relational. A creator continuously: perceives opportunities, interprets unfolding conditions, acts within a system, receives feedback, and reorganizes understanding through interaction.
Creativity therefore becomes a living process of adaptive participation. This perspective draws heavily from: enactive cognition, ecological psychology, participatory sense-making, improvisation studies, and adaptive systems theory. From this viewpoint, creative systems are not static generators of output. They are dynamically coupled participants engaged in ongoing processes of mutual transformation.
The concept of “sense-making” originates from enactive cognitive science and refers to the process through which an organism brings forth meaning through active engagement with its environment.
Meaning is not passively received from the world. Nor is it fully preconstructed internally. Instead, meaning emerges through interaction. Creative Sense-Making extends this principle into creative collaboration. During creative activity: perception changes action, action changes the environment, environmental change reorganizes perception, and new possibilities emerge recursively. This process creates a continuously evolving field of affordances — opportunities for action, interpretation, and transformation. Creativity therefore becomes a process of navigating and reshaping these evolving affordance landscapes.
Creative Sense-Making became particularly important in the study of co-creative AI systems. Traditional AI systems are often evaluated as tools: generators, assistants, or autonomous creators. Co-creative systems are different. A co-creative system participates in the creative process alongside a human collaborator. The interaction itself becomes part of the creative outcome.
In these systems: the human adapts to the AI, the AI influences the human, the interaction evolves over time, and creativity emerges from the coupled system rather than either participant alone. This led to an important realization:
The quality of creativity often depends less on isolated intelligence and more on interaction dynamics.
Creative Sense-Making therefore studies: interaction rhythms, feedback loops, breakdown and recovery, adaptive alignment, shared attention, and the emergence of mutual creative trajectories.
A core insight of the framework is that creative interaction is inherently unstable and emergent. Creative systems continuously drift as: goals evolve, interpretations shift, environments change, and participants adapt. This means creativity cannot be fully reduced to: predefined rules, static representations, or fixed optimization targets. Instead, creative systems remain alive precisely because they remain open to reorganization. Moments of surprise, insight, novelty, and discovery emerge when interaction reorganizes perception in unexpected but coherent ways.
In this sense, creativity is not simply invention.
It is adaptive emergence.
One contribution of the Creative Sense-Making framework was the attempt to analyze and quantify the dynamics of co-creative interaction itself. Rather than evaluating only final artifacts, the framework investigated:
interaction patterns,
turn-taking,
influence shifts,
collaborative trajectories,
and evolving participation structures.
This allowed creativity to be studied not merely as output quality, but as an unfolding process of coupled cognition. The focus therefore shifted from:
“Did the system create something creative?”
to:
“How did creativity emerge through interaction?”
This distinction remains increasingly important in modern human-AI collaboration research.
As AI systems become more interactive, adaptive, and collaborative, Creative Sense-Making becomes increasingly relevant. Many current AI systems still operate primarily as generators: producing outputs, predicting responses, or optimizing tasks. But future collaborative systems may function more like participatory partners: adapting over time, co-regulating interaction, supporting exploration, and reshaping human cognition through sustained engagement. Creative Sense-Making provides a framework for understanding these interaction-centered futures.
Rather than asking:
“Can AI replace human creativity?”
the framework asks:
“How do humans and intelligent systems participate in shared processes of meaning creation?”
This shift moves creativity away from isolated production and toward collaborative emergence.
Ultimately, Creative Sense-Making proposes that creativity is not an object contained within individuals or machines. Creativity is a relational process emerging through participation in evolving systems.
Ideas arise through interaction.
Meaning emerges through engagement.
Novelty appears through adaptive coupling.
Creativity is therefore not simply something we possess. It is something we enact together.
Abstract
This paper describes a new technique for quantifying interaction dynamics during open-ended co-creation, such as collaborative drawing or playing pretend. We present a cognitive framework called creative sense-making. This framework synthesizes existing cognitive science theories and empirical investigations into open-ended improvisation to develop a method of quantifying cognitive states and types of interactions through time. We apply this framework to empirical studies of human collaboration (in the domain of pretend play) and AI-based systems (in the domain of collaborative drawing) to establish its validity through cross-domain application and inter-rater reliability within each domain. The creative sense-making framework described includes a qualitative coding technique, interaction coding software, and the cognitive theory behind their application.
Abstract
The field of computational creativity is beginning to investigate how co-creative agents might interface with the human creative process. These computer colleagues are a mix between creativity support tools helping users achieve creative goals and creative algorithms that generate content autonomously. Computer colleagues have enormous potential because during creative improvisational collaboration, a new form of distributed creativity arises that can lead to emergent, dynamic, and unexpected meaning to support creativity in new ways. However, there is a gap in the literature about cognitive accounts of the interaction dynamics of open-ended creative collab- oration, e.g. the rhythm of interaction, style of turn taking, and manner in which participants are mutually making sense of a situation. An empirically grounded cogni- tive framework would greatly aid in the design and evaluation of co-creative systems. With this dissertation, I begin to address that gap by asking the overarching research question: How do humans collaborate in open-ended improvisational creativity, and how can we design co-creative agents to achieve similar benefits as human collaboration?