I am a researcher and designer working at the intersection of cognitive science, creativity research, human-computer interaction, and artificial intelligence. My work focuses on understanding how creativity, meaning, and intelligence emerge through interaction between people, technologies, and environments.
I received my PhD in Human-Centered Computing from the Georgia Institute of Technology in 2017, specializing in Cognitive Science and Computational Creativity. My doctoral research introduced the Creative Sense-Making framework, a cognitive theory and methodology for understanding creativity as an emergent process of interaction and participatory sense-making. This work led to the development of Sense-Making Curves, Quantified Co-Creation, and new methods for analyzing the dynamics of collaborative creativity through time.
Following my doctoral work, I served as an Assistant Professor in Human-Computer Interaction at the University of North Carolina at Charlotte, where I conducted research on co-creative AI systems, creativity support tools, and human-AI collaboration. My research has explored how intelligent systems can participate in creative processes as collaborative partners rather than simply functioning as autonomous generators or passive tools.
My research spans several interconnected areas:
Creative Sense-Making
Human-AI Co-Creation
Computational Creativity
Cognitive Science
Human-Computer Interaction
Interaction Dynamics
Quantified Co-Creation
Participatory Sense-Making
Enactive Cognition
Adaptive Interactive Systems
Creativity Support Tools
Interaction-Centered Intelligence
Across these domains, a central question motivates my work:
How do people, technologies, and environments participate together in the emergence of meaning, novelty, creativity, and intelligence?
My current work is organized across the following interconnected initiatives.
Creative Sense-Making is the foundational theoretical framework underlying much of my research. It investigates creativity as an emergent process of interaction and provides methods for visualizing and quantifying interaction dynamics through time. The framework includes Sense-Making Curves, Quantified Co-Creation, interaction coding methodologies, and analytical tools for studying collaborative creativity.
Co-Creative AI explores how humans and intelligent systems can collaborate in creative processes. This work includes research prototypes such as Drawing Apprentice and AI Drawing Partner, as well as theoretical work on interaction-centered intelligence, participatory cognition, and the future of human-AI collaboration.
Quantified Co-Creation is a methodological framework for measuring, visualizing, and analyzing creative interaction as it unfolds through time. Rather than focusing solely on final creative products, the framework examines activity traces, interaction dynamics, participation patterns, and collaborative trajectories to better understand how creativity emerges through interaction. Building upon Creative Sense-Making, Quantified Co-Creation provides researchers with tools for studying human-human and human-AI collaboration as observable and measurable processes.
Sense-Making Curves are visual representations of interaction trajectories through time. By transforming coded interaction events into continuous trajectories, the curves reveal patterns of exploration, coordination, divergence, convergence, and creative emergence that may otherwise remain hidden within complex collaborative processes. They provide a way to visualize how sense-making evolves during creative activity and serve as one of the central analytical tools within the Creative Sense-Making framework.
The Analysis Framework provides a structured approach for investigating creative interaction across multiple dimensions. It includes Cognitive Dynamics (how participants think and regulate activity), Interaction Dynamics (how participants communicate and coordinate), Collaboration Dynamics (how novelty emerges through participation), and Domain Behaviors (the specific actions performed within a creative domain). Together, these analytical lenses allow researchers to move beyond evaluating outcomes alone and examine the underlying processes through which creativity, meaning, and co-creation emerge.
Cognitive Druidry extends these ideas into a broader philosophical and practical framework that integrates cognition, creativity, participation, perception, meaning-making, and human flourishing. It serves as an accessible gateway for exploring many of the concepts developed throughout the research program.
Before entering academia, I earned a Bachelor of Arts in Cognitive Science from Case Western Reserve University. During my career I have conducted research at Georgia Tech's Expressive Machinery Lab, worked on interactive AI systems, and collaborated with industry organizations including Google, YouTube, and Adobe. My work has focused consistently on understanding creativity and intelligence as fundamentally interactive phenomena rather than isolated processes occurring solely within individuals.
Creative Sense-Making
CreativeSense-Making.com
Co-Creative AI
Co-CreativeAI.com
Academic Website
NickMDavis.com
For research collaborations, speaking engagements, academic inquiries, or discussions related to Creative Sense-Making, Co-Creative AI, Human-AI Collaboration, or Cognitive Druidry, please feel free to reach out.
nicholas.davis10@gmail.com
© Nicholas Davis 2022