The Foundations section brings together the core theories, publications, cognitive frameworks, and research trajectories that underpin more than a decade of interdisciplinary research in co-creative artificial intelligence, computational creativity, human-computer interaction, enactive cognition, participatory sense-making, adaptive systems, and human-centered AI.
At its center is a simple but transformative question:
What happens when intelligence is understood not as isolated computation within individuals, but as something that emerges through interaction between participants?
This question motivated a long-running research program exploring how humans and AI systems can collaborate as creative partners in shared processes of exploration, meaning-making, problem solving, and innovation. Beginning with early investigations into human-computer co-creativity and computational collaboration, this work gradually evolved into a broader interaction-centered paradigm for understanding creativity, intelligence, and human-AI collaboration.
Rather than presenting a collection of disconnected papers, the Foundations section traces the historical development of a coherent research lineage. Across multiple projects, publications, and theoretical frameworks, a recurring theme emerges: creativity and intelligence are not solely properties of individuals, algorithms, or artifacts. They arise through ongoing participation, adaptation, and coordination between interacting agents.
Many of the ideas presented here originated through early work on co-creative drawing systems such as The Drawing Apprentice, one of the earliest AI systems designed to collaborate with users in real-time artistic interaction. These systems served not only as creative tools, but also as experimental platforms for investigating how collaboration unfolds through turn-taking, improvisation, feedback, coordination, and shared sense-making.
Over time, this research expanded beyond computational creativity into broader questions concerning human-AI interaction, hybrid intelligence, explainable co-creative systems, adaptive collaboration, participatory cognition, and enactive approaches to artificial intelligence. This progression led to the development of several interconnected frameworks, including:
Creative Sense-Making — a framework for modeling and quantifying the dynamics of co-creative interaction through time.
Quantified Co-Creation — approaches for measuring activity traces, creative trajectories, interaction dynamics, and collaborative emergence.
Human-AI Co-Creation — a paradigm in which humans and AI systems participate together in shared creative and cognitive processes.
Participatory Sense-Making in AI Systems — extending enactive theories of social cognition into human-AI interaction.
Enactive AI — an interaction-centered approach to artificial intelligence grounded in autonomy, emergence, embodiment, sense-making, and experience.
Interaction-Centered Intelligence — a broader framework proposing interaction itself as the primary unit of analysis for understanding intelligence in human-AI systems.
Collectively, these works helped contribute to a growing shift within AI research away from purely output-centered perspectives and toward relational, participatory, and interaction-centered approaches. Rather than viewing AI solely as a tool, generator, optimizer, or autonomous agent, this research explores AI as a collaborative participant capable of engaging in shared processes of creativity, adaptation, and sense-making.
Today, many of these ideas resonate with emerging conversations surrounding hybrid intelligence, explainable AI, human-centered AI, and collaborative generative systems. The Foundations section provides the conceptual background necessary to understand how these developments emerged, where they originated, and how they connect to the broader vision of interaction-centered artificial intelligence.
Together, the publications, essays, and frameworks collected here document the evolution of a research program dedicated to understanding one central proposition:
Intelligence is not merely something that exists within humans or machines. It emerges through interaction between them.
These ideas emerged alongside and contributed to broader developments in co-creative AI, mixed-initiative systems, human-AI collaboration, and hybrid intelligence. As generative AI systems become increasingly integrated into creative and knowledge work, understanding the dynamics of interaction, participation, and collaborative sense-making becomes increasingly important for the future of human-AI partnership.