Research and Publications
The effects of AI can neither be understood nor well designed by looking at the technology alone. I therefore take a sociotechnical perspective in all my work: people encounter AI systems in a particular context of use, and all three have to be thought about together — anyone who wants to understand, design and properly evaluate human-AI interaction cannot ignore any of them.
My research focuses on the following questions: How do people stay in control of AI systems? How does work with AI have to be designed so that it remains good work for everyone involved — for those who work with the systems, and for those affected by AI decisions? And what does the use of these systems do to us: to our judgement, our collaboration, our well-being? Responsibility is the common thread: it is what distinguishes humans from machines, and responsible AI design means building and deploying systems in a way that people can actually carry that responsibility.
The problems of the AI age cannot be handled from within a single discipline. I work in close exchange with computer science, ethics and law, and therefore publish not only in psychology and computer science but also in interdisciplinary journals beyond them. The strength of the psychological perspective is that it works independently of the context of use and of the current state of the technology: people change more slowly than technology does — and that is precisely what makes psychology a tool for understanding technology and its effects in a way that lasts.
Research areas
Human oversight and control of AI
How do people stay in control of systems that handle tasks faster — and increasingly better — than they do themselves? How do you recognise risks in time, and what is your own contribution when the machine is usually right; in other words, what is the role of humans in the work of the future? Trust and explainability belong here, as does my work on the regulation of AI.
Selected publications
- Hunsicker, T., Schulz, A., Leist, R. A., Kiefer, S., Boden, K. T., Rothaus, K., König, C. J., & Langer, M. (2026). Explanations as time-efficiency pitfalls in AI-assisted clinical decision-making. Human Factors. doi:10.1177/00187208261443764
- Schlicker, N., Baum, K., Uhde, A., Sterz, S., Hirsch, M., & Langer, M. (2025). How do we assess the trustworthiness of AI? Introducing the Trustworthiness Assessment Model (TrAM). Computers in Human Behavior, 170, Article 108671. doi:10.1016/j.chb.2025.108671
- Sterz, S., Baum, K., Biewer, S., Hermanns, H., Meinel, P., Lauber-Rönsberg, A., & Langer, M. (2024). On the quest for effectiveness in human oversight: Interdisciplinary perspectives. Proceedings of the FAccT Conference on Fairness, Accountability, and Transparency. doi:10.1145/3630106.3659051
- Langer, M., König, C. J., Back, C., & Hemsing, V. (2023). Trust in Artificial Intelligence: Comparing trust processes between human and automated trustees in light of unfair bias. Journal of Business and Psychology, 38(3), 493–508. doi:10.1007/s10869-022-09829-9
- Langer, M., Oster, D., Speith, T., Hermanns, H., Kästner, L., Schmidt, E., Sesing, A., & Baum, K. (2021). What do we want from Explainable Artificial Intelligence (XAI)? A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research. Artificial Intelligence, 296, 103473. doi:10.1016/j.artint.2021.103473 Shared first authorship with Daniel Oster and Timo Speith.
Good work with AI
If nothing is done, the future of work may well turn out to be an unpleasant one. Work with AI has to be designed so that it becomes human-centred, good work — work that preserves or even promotes health and well-being. Good design has to bring several perspectives together: that of the people using AI systems, and that of the people affected by AI-based decisions. I am interested in what responsible design and use look like when they contribute to long-term human well-being.
Selected publications
- Langer, M., & Kluge, A. (2026). Auswirkungen von KI auf psychische Belastung in der Arbeitswelt. White paper for the German statutory accident insurance institution VBG. doi:10.31234/osf.io/a4svx_v1
- Kares, F., Hannig, L., & Langer, M. (2026). Working with Large Language Models: Impacts on performance, efficiency and perceived responsibility. Behaviour and Information Technology. doi:10.1080/0144929X.2026.2666279
- Ohlms, M. L., Dunlop, P., & Langer, M. (2026). Effects of AI-based chatbot coaching on goal attainment, self-efficacy, and stress: A longitudinal randomized experiment. Computers in Human Behavior, 187, Article 109184. doi:10.1016/j.chb.2026.109184
- Langer, M., & Landers, R. N. (2021). Artificial intelligence at work: A review on effects of decision automation and augmentation on people targeted by algorithms, and third-party observers. Computers in Human Behavior, 123, 106878. doi:10.1016/j.chb.2021.106878
- Langer, M., König, C. J., & Busch, V. (2021). Changing the means of managerial work: Effects of automated decision-support systems on personnel selection tasks. Journal of Business and Psychology, 36(5), 751–769. doi:10.1007/s10869-020-09711-6
Societal effects of AI and responsible AI design
What does the use of AI do to us as a society — to our judgement, our life together, and our trust in institutions? And what is the role of psychology for the future of AI in society and in research?
Selected publications
- Bigman, Y. E., Briker, R., & Langer, M. (2026). Human–AI interaction research needs to be embedded in psychological theory. Nature Reviews Psychology, 5, 233–234. doi:10.1038/s44159-026-00551-4
- Meinel, P., Baum, K., Hermanns, H., Lauber-Rönsberg, A., & Langer, M. (2026). Human oversight of AI agents in the EU AI Act. Cambridge Forum on AI: Law and Governance.
- Caroei, A. S., Brodowski, D., Grabmair, M., Koçak, A., Kolbe, M., Olheide, J., Paschke, A., … & Langer, M. (2026). KI-Einsatz im deutschen Justizsystem – Ergebnisse einer empirischen Untersuchung. MMR – Zeitschrift für das Recht der Digitalisierung, Datenwirtschaft und IT, 619–629.
- Langer, M., Lazar, V., & Baum, K. (2025). On the complexities of testing for compliance with human oversight requirements in AI regulation. Lecture Notes in Computer Science: Proceedings of the AISoLA Conference. doi:10.1007/978-3-032-07132-3_11
- Lima, G., Grgić-Hlača, N., Langer, M., & Zou, Y. (2025). Lay perceptions of algorithmic discrimination in the context of systemic injustice. Proceedings of the CHI Conference on Human Factors in Computing Systems. doi:10.1145/3706598.3713536 Honorable Mention — top 5 % of submissions.
Books
All publications
My complete publication list is available on Google Scholar.
All publications on Google Scholar