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An Empirical Evaluation of Predicted Outcomes as Explanations in Human-AI Decision-Making., , , , и . PKDD/ECML Workshops (1), том 1752 из Communications in Computer and Information Science, стр. 353-368. Springer, (2022)DEAL: Deep Evidential Active Learning for Image Classification., , и . ICMLA, стр. 865-870. IEEE, (2020)Appropriate Fairness Perceptions? On the Effectiveness of Explanations in Enabling People to Assess the Fairness of Automated Decision Systems., и . CSCW Companion, стр. 153-157. ACM, (2021)Utilizing Adaptive AI-based Information Systems to Analyze the Effectiveness of Policy Measures in the Fight of COVID-19., , и . ICIS, Association for Information Systems, (2020)Utilizing Concept Drift for Measuring the Effectiveness of Policy Interventions: The Case of the COVID-19 Pandemic., , , и . CoRR, (2020)A Study on Fairness and Trust Perceptions in Automated Decision Making., , и . IUI Workshops, том 2903 из CEUR Workshop Proceedings, CEUR-WS.org, (2021)A Ranking Approach to Fair Classification., , и . COMPASS, стр. 115-125. ACM, (2021)Mapping the Potential of Explainable Artificial Intelligence (XAI) for Fairness Along the AI Lifecycle., , , , , и . CoRR, (2024)