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    Item type:Publication, Access status: with files ,
    A taxonomy of AI experiments
    (Elsevier, 2026-01-22)
    Alekseev, Aleksandr
    ;
    Strobel, Christina
    We introduce a taxonomy of artificial intelligence (AI) experiments. Our taxonomy produces four types of AI experiments: conceptual AI experiments, stylized AI experiments, quasi-natural AI experiments, and natural AI experiments. At the core of our taxonomy is the sophistication of AI used, which we evaluate using a simple and robust proxy test of whether AI is developed exclusively for a research study. We discuss the advantages, disadvantages, and best use cases for each type and illustrate the use of each type in various examples. We provide a guide on how to choose the type of AI experiment that best fits a given research question.
    Publicationtype: Journal Article
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    The impact of process automation on performance
    (2025-05-19)
    Strobel, Christina
    This paper explores how process automation affects performance, particularly in bonus-related evaluations. Using a principal–agent framework, we study the impact of predefined criteria set during system design. Specifically, we examine two scenarios in which the performance threshold for bonus payments is set either ex-ante (before performance is known) or ex-post (after performance is known). Worker performance is measured using the chosen-effort method. Our design emphasizes the role of the decision-maker in the automation process, while also considering the influence of process fairness, trust in the process, and expectations. We find that performance is significantly lower when an automated process is used, but there is no difference in performance based on who makes the decision to automate. Furthermore, we observe no variation in perceived fairness or trust between the two processes, although expectations differ. Our results suggest that while automation impacts performance, the decision-maker’s role and perceptions of fairness and trust do not significantly affect the performance, but expectations do.
    Publicationtype: Journal Article
      53  24