Ghosts in the machine. We study the provenance gap and look for ways to surface and trace the priors that shape AI performance and outputs.

Proof of life. Provenance gaps flow from model capabilities, standards of evidence, and trust in data. What counts as truth, and why?

As we may think. Our research deals with the locus of intelligence, in philosophical and applied terms, in human-machine systems.