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Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability., , , и . Int. J. Inf. Manag., (апреля 2023)Artificial Intelligence for Human Decision-Makers: Systematization, Perception, and Adoption of Intelligent Decision Support Systems in Industry 4.0.. Julius Maximilians University Würzburg, Germany, (2022)A Moral Consensus Mechanism for Autonomous Driving: Towards a Law-compliant Basis of Logic Programming., , , , и . Wirtschaftsinformatik (Zentrale Tracks), стр. 17-32. GITO Verlag, (2020)A Social Evaluation of the Perceived Goodness of Explainability in Machine Learning, , , и . Journal of Business Analytics, 5 (1): 29-50 (2022)The effect of transparency and trust on intelligent system acceptance: Evidence from a user-based study., , , и . Electron. Mark., 32 (4): 2079-2102 (декабря 2022)Design Principles for Shared Maintenance Analytics in Fleet Management., , и . DESRIST, том 12807 из Lecture Notes in Computer Science, стр. 236-247. Springer, (2021)White, Grey, Black: Effects of XAI Augmentation on the Confidence in AI-based Decision Support Systems, , , и . (2020)How Much Is the Black Box? The Value of Explainability in Machine Learning Models, , и . 28th European Conference on Information Systems (ECIS), стр. 1-14. AIS Virtual Conference Series, AIS, (2020)Two-Sided Digital Markets: Disruptive Chance Meets Chicken or Egg Causality Dilemma, , и . 21st IEEE Conference on Business Informatics (CBI), стр. 335-344. Moscow, IEEE, (2019)Adoption Barriers of AI: A Context-Specific Acceptance Model for Industrial Maintenance, , , , и . 29h European Conference on Information Systems (ECIS), стр. 1-13. AIS Virtual Conference Series, AIS, (2021)