Kantian-Utilitarian XAI: Meta-Explained

The system uses two complementary ethical frameworks to guide choices: A Kantian module identifies absolute rule violations (child labor, deforestation without certification, opaque supply chains), while a utilitarian module weighs trade-offs across multiple factors like price, carbon footprint, water use, and farmer income. This dual approach acknowledges that ethical decisions often involve competing values.

The system is designed to be transparent and auditable: The researchers released their configuration schema, certification maps, decision weights, and policy traces publicly. This means users and external reviewers can examine exactly how recommendations are being made—a key requirement for responsible AI systems that make ethical claims.

The meta-explainer addresses a practical ethical problem: When Kantian rules (absolute ethical standards) and utilitarian optimization (maximizing overall welfare) disagree, the system explicitly highlights this conflict and can recommend a "deontically clean" option with minimal welfare loss. This prevents users from unknowingly compromising core ethical principles for marginal benefits.

The system quantifies acceptable trade-offs with a regret bound: By setting a 0.2 regret bound, the designers formalized how much welfare loss is acceptable when switching from the utilitarian-optimal choice to an ethically cleaner option—making the implicit value judgment explicit rather than hidden.

The gamified format may improve ethical engagement: By structuring the coffee purchasing task as a six-round game with real-time explanations, the system attempts to make ethical decision-making interactive and engaging rather than burdensome, potentially increasing user adoption of responsible choices.