Interactive Evaluation Requires a Design Science

A new paper argues that interactive AI needs its own evaluation paradigm, not just static benchmarks.

It proposes a design-science framework with a taxonomy, design principles, and reporting standards.

The framework scores system behavior across dynamic interaction trajectories instead of single responses.

This matters because real-world AI systems must coordinate, adapt, and stay robust over time.