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Energy Shields for Fairness

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#artificial intelligence#fairness#decision-making
Energy Shields for Fairness
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The paper titled 'Energy Shields for Fairness' introduces a novel approach to ensuring runtime fairness in decision-making processes. It presents energy shields as adaptive controllers that intervene probabilistically to maintain fairness over time. This method aims to provide both short-term safety and long-term liveness guarantees in fairness measures.

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arXiv cs.AI
Read full at arXiv cs.AI →
Opening excerpt (first ~120 words) tap to expand

Computer Science > Artificial Intelligence arXiv:2605.24926 (cs) [Submitted on 24 May 2026] Title:Energy Shields for Fairness Authors:Filip Cano, Thomas A. Henzinger, Konstantin Kueffner View a PDF of the paper titled Energy Shields for Fairness, by Filip Cano and Thomas A. Henzinger and Konstantin Kueffner View PDF HTML (experimental) Abstract:Runtime fairness is not a one-time constraint but a dynamic property evaluated over a sequence of decisions. To ensure fairness at runtime, it is necessary to account for past decisions, information neglected by conventional, static classifiers. Traditional fairness shields enforce runtime fairness abruptly, by intervening \emph{deterministically} whenever a sequence of decisions violates the target for a running fairness measure.

Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.

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