In scientific research, identifying the causal agent is critical for developing interventions.
In modern technology, "Causal Agents" refer to specialized AI systems designed to understand and act upon cause-and-effect relationships rather than just simple patterns. causal agent
Unlike standard AI which is often reactive, Agentic AI with causal understanding can anticipate the consequences of its actions and identify the true mechanisms behind data trends (e.g., recognizing that "stress" is the real cause of weight gain during exams, not the exams themselves) [25, 35]. In scientific research, identifying the causal agent is