Autonomous AI research systems are increasingly organized around process transparency. Long-running agents are now expected to decompose problems, manage subtasks, expose intermediate reasoning traces, and generate scientific outputs with reduced human oversight. This shift from opaque black-box models to partially inspectable systems represents a genuine governance advance.
Peter Bell (Sat,) studied this question.