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Promotes ethical AI by ensuring models are fair, interpretable, and responsible. Addresses biases and builds trust in AI systems.
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 Multistakeholder Fairness in Tourism: What can Algorithms learn from Tourism Management?Frontiers in Big Data (FBD), 2025 | |||
 Applications and Challenges of Fairness APIs in Machine Learning SoftwareACM Transactions on Software Engineering and Methodology (TOSEM), 2025 | |||
 Algorithmic Fairness: A Runtime PerspectiveRuntime Verification (RV), 2025 | |||
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 Guiding LLM Decision-Making with Fairness Reward Models Zara Hall Melanie Subbiah Thomas P Zollo Kathleen McKeown Richard Zemel | |||
 Monitoring of Static Fairness Thomas A. Henzinger Mahyar Karimi Konstantin Kueffner Kaushik Mallik | |||
 Consumer Beware! Exploring Data Brokers' CCPA Compliance Elina van Kempen Isita Bagayatkar Pavel Frolikov Chloe Georgiou Gene Tsudik | |||
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