Exploring the textures of experience at the intersection of Artificial Intelligence, the Philosophy of Mind, and the Phenomenology of Time.
TimeQualia is a long‑form research and creation project investigating how intelligent systems perceive, model, and generate qualia—the felt qualities of experience—and how those experiences unfold in subjective time. We combine tools from machine learning and cognitive science with questions from analytic and continental philosophy: What does it mean for an artificial system to feel like something? Can temporal structure—rhythm, delay, anticipation—shape cognition in ways we can measure or even design? And how might new models of time help us build systems that are safer, more transparent, and more humane?
Across essays, prototypes, and experiments we will: (1) map theoretical landscapes spanning computational theories of mind, representation learning, and consciousness studies; (2) prototype AI that manipulates temporal representations—intervals, durations, narratives—to capture the grain of lived experience; and (3) open‑source tools, datasets, and visualizations to invite rigorous public collaboration.
We explore architectures—from sequence models to world simulators—that learn temporal and sensory manifolds, asking how internal representations might correlate with reportable qualia.
Beyond what states represent lies how they feel. We test notions like higher‑order thought, global workspace, and predictive processing against computational evidence.
Subjective time is elastic. We study temporal granularity—windows, buffers, and rhythms—as design levers for attention, memory, and agency in humans and machines.
We translate theory into practice with guidance for interpretable models, value‑sensitive design, and experiment protocols that guard against harm to people and systems.