  Generative Artificial Intelligence (AI) models can propose solutions to
scientific problems beyond human capability. To truly make conceptual
contributions, researchers need to be capable of understanding the AI-generated
structures and extracting the underlying concepts and ideas. When algorithms
provide little explanatory reasoning alongside the output, scientists have to
reverse-engineer the fundamental insights behind proposals based solely on
examples. This task can be challenging as the output is often highly complex
and thus not immediately accessible to humans. In this work we show how
transferring part of the analysis process into an immersive Virtual Reality
(VR) environment can assist researchers in developing an understanding of
AI-generated solutions. We demonstrate the usefulness of VR in finding
interpretable configurations of abstract graphs, representing Quantum Optics
experiments. Thereby, we can manually discover new generalizations of
AI-discoveries as well as new understanding in experimental quantum optics.
Furthermore, it allows us to customize the search space in an informed way - as
a human-in-the-loop - to achieve significantly faster subsequent discovery
iterations. As concrete examples, with this technology, we discover a new
resource-efficient 3-dimensional entanglement swapping scheme, as well as a
3-dimensional 4-particle Greenberger-Horne-Zeilinger-state analyzer. Our
results show the potential of VR for increasing a human researcher's ability to
derive knowledge from graph-based generative AI that, which is a common
abstract data representation used in diverse fields of science.
