For a claim of causation to be valid, there must be a correlation between the cause and effect, the effect must follow the cause chronologically, and there should be a plausible explanation for the process [11].
The most reliable way to identify a causal agent is through randomized controlled experiments (such as A/B tests), where one group receives a "treatment" from the agent and another does not [12]. 2. Applications in Artificial Intelligence
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]. causal agent
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.
By encoding causal links into their decision-making processes, AI agents can navigate complex environments more safely and handle "distribution shifts" (changes in environment rules) more effectively [22, 10]. 3. Causal Agents in Health and Science For a claim of causation to be valid,
At its core, a causal agent is a "thing" with the power to change the world by causing an effect [20].
Researchers look for causal agents to determine if an intervention should be applied to the subject (like a vaccine) or the agent itself (like boiling contaminated water) [17]. not the exams themselves) [25
A is an entity or force responsible for producing a specific effect or outcome. In various fields, it serves as the "bridge" between an initial condition and a final result. 1. General Concepts
