In algorithmic decision environments, humans make decisions under uncertainty based on information that has been personalized for them using algorithms (e.g. scoring values, social networks). Based on their features, how do algorithmic decision environments (1) affect decision making, understanding, and memory, (2) what kind of presentation enables an informed use, and (3) which competencies are required for a controlled interaction with an algorithmic decision environment? We investigate psychological prerequisites for citizens to be able to control algorithmic decision environments individually or through regulation.
Examples
Rebitschek, F. G., Carella, A., Kohlrausch-Pazin, S., Zitzmann, M., Steckelberg, A., & Wilhelm, C. (2025). Evaluating evidence-based health information from generative AI using a cross-sectional study with laypeople seeking screening information. npj Digital Medicine, 8, 343, 1-8. https://doi.org/10.1038/s41746-025-01752-6.
Wilhelm, C., Steckelberg, A, & Rebitschek, F. G. (2025). Benefits and harms associated with the use of AI-related algorithmic decision-making systems by healthcare professionals: a systematic review. The Lancet: Regional Health Europe, 48, 101145. https://doi.org/10.1016/j.lanepe.2024.101145.
Wilhelm, C., Steckelberg, A., & Rebitschek, F. G. (2024). Is artificial intelligence for medical professionals serving the patients? Protocol for a mixed method systematic review on patient-relevant benefits and harms of algorithmic decision-making. BMC Systematic Reviews, 13(228), 1-10. https://doi.org/10.1186/s13643-024-02646-6.
Rebitschek, F. G., Gigerenzer, G., & Wagner, G. G. (2021). People underestimate the errors made by algorithms for credit scoring and recidivism prediction but accept even fewer errors. Nature Scientific Reports. 11: 20171. https://doi.org/10.1038/s41598-021-99802-y.
Rebitschek, F. G., Gigerenzer, G., Keitel, A., Sommer, S., Groß, C., & Wagner, G. G. (2021). Acceptance of criteria for health and driver scoring in the general public in Germany. PLOS ONE. 16(4): e0250224. https://doi.org/10.1371/journal.pone.0250224.
Rebitschek, F. G., & Wagner, G. G. (2020). Zur Akzeptanz von assistiven Robotern im Pflege- und Gesundheitsbereich: Repräsentative Daten zeichnen ein klares Bild für Deutschland [Acceptance of assistive robots in the field of nursing and healthcare : Representative data show a clear picture for Germany]. Zeitschrift für Gerontologie und Geriatrie, 53, 637–643. https://doi.org/10.1007/s00391-020-01780-9.
Rebitschek, F. G., & Gigerenzer, G. (2020). Einschätzung der Qualität digitaler Gesundheitsangebote: Wie können informierte Entscheidungen gefördert werden? [Assessing the quality of digital health services: How can informed decisions be promoted?] Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz, 63(6), 665-673. https://doi.org/10.1007/s00103-020-03146-3.