kaal:position:2026-07-31-7626
Explainable AI Models for Ethical Marketing presents the following source proposition: To be transparent and interpretable to the regulators, the system integrates global and local explanations based on SHAP with the generation of counterfactual. This proposition is pertinent to Kaal's source-bound claim that Explainable reinforcement learning research has not yet produced usable explanations: the field relies on toy examples, omits user testing, produces explanations that are themselves complex, uses basic visualizations, and rarely open sources its code. The proposed response is an extension: the relationship should remain limited to the retrieved source proposition and the mapped Kaal claim unless fuller source review supports a broader conclusion.
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