AI agents help explain other AI systems

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a unique approach to conduct experiments on AI systems and explain their behaviour. They have created an “automated interpretability agent” (AIA) that emulates the experimental processes of a scientist. The AIA actively participates in hypothesis formation, experimental testing, and iterative learning, thus refining its understanding of other systems in real time. To evaluate the quality of descriptions of real-world network components, the team has developed the FIND benchmark, which provides a reliable standard for assessing interpretability procedures.

Source: MIT