As AI becomes more deeply embedded in clinical workflows, the question is no longer whether to trust the machine — it's who is responsible when something goes wrong. This session examines what the human-AI control boundary looks like in practice: how clinicians maintain meaningful oversight when algorithms move faster than human cognition, how institutions are defining accountability in the absence of clear regulation, and what it truly means to keep the human in the loop. Through peer conversation and shared problem-solving, participants will challenge their own assumptions about control and responsibility — and leave with a clearer sense of what they will do differently when they return to practice.

This workshop is designed to move discussion into real-world action. Each session creates space for meaningful conversation, peer learning, and shared problem-solving, with a clear focus on what happens after the event. Participants will be encouraged to continue the dialogue beyond the room by sharing reflections, resources, and follow-up actions via a dedicated WhatsApp group. By building these connections, the Action Lab helps turn a one-off session into an ongoing community of practice.