Causal inference frameworks help identify and model cause-effect relationships within agentic AI decision-making processes. By understanding the causal pathways, these frameworks allow for assigning responsibility and accountability by distinguishing outcomes caused by the AI agent from those due to external factors or stochasticity.
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