publications

2026

1. 

   Design Considerations for Human Oversight of AI: Insights from Co-Design Workshops and Work Design Theory

   Cedric Faas, Sophie Kerstan, Richard Uth, Markus Langer, and Anna Maria Feit

   Mar 2026

   Abs DOI arXiv Bib PDF

   As AI systems become increasingly capable and autonomous, domain experts’ roles are shifting from performing tasks themselves to overseeing AI-generated outputs. Such oversight is critical, as undetected errors can have serious consequences or undermine the benefits of AI. Effective oversight, however, depends not only on detecting and correcting AI errors but also on the motivation and engagement of the oversight personnel and the meaningfulness they see in their work. Yet little is known about how domain experts approach and experience the oversight task and what should be considered to design effective and motivational interfaces that support human oversight. To address these questions, we conducted four co-design workshops with domain experts from psychology and computer science. We asked them to first oversee an AI-based grading system, and then discuss their experiences and needs during oversight. Finally, they collaboratively prototyped interfaces that could support them in their oversight task. Our thematic analysis revealed four key user requirements: understanding tasks and responsibilities, gaining insight into the AI’s decision-making, contributing meaningfully to the process, and collaborating with peers and the AI. We integrated these empirical insights with the SMART model of work design to develop a framework of twelve design considerations with increased transferability compared to the identified user requirements. Our framework links interface characteristics and user requirements to the psychological processes underlying effective and satisfying work. Being grounded in work design theory and overlapping with existing guidelines for human–AI interaction, we expect these considerations to be applicable across domains and discuss how they go beyond existing guidelines for human-AI interaction to inform the design of engaging and meaningful interfaces that support human oversight of AI-based systems.

   @misc{faas2025designconsiderationshumanoversight,
     address = {New York, NY, USA},
     series = {{IUI} '26},
     title = {Design {Considerations} for {Human} {Oversight} of {AI}: {Insights} from {Co}-{Design} {Workshops} and {Work} {Design} {Theory}},
     isbn = {979-8-4007-1984-4},
     shorttitle = {Design {Considerations} for {Human} {Oversight} of {AI}},
     url = {https://dl.acm.org/doi/10.1145/3742413.3789100},
     doi = {10.1145/3742413.3789100},
     urldate = {2026-04-27},
     booktitle = {Proceedings of the 31st {International} {Conference} on {Intelligent} {User} {Interfaces}},
     publisher = {Association for Computing Machinery},
     author = {Faas, Cedric and Kerstan, Sophie and Uth, Richard and Langer, Markus and Feit, Anna Maria},
     month = mar,
     year = {2026},
     pages = {804--821},
   }

2. 

   Don’t blame me: How Intelligent Support Affects Moral Responsibility in Human Oversight

   Cedric Faas, Richard Uth, Sarah Sterz, Markus Langer, and Anna Maria Feit

   Feb 2026

   DOI arXiv Bib PDF

   @misc{faas_dont_2026,
     title = {Don't blame me: {How} {Intelligent} {Support} {Affects} {Moral} {Responsibility} in {Human} {Oversight}},
     shorttitle = {Don't blame me},
     url = {http://arxiv.org/abs/2602.10701},
     doi = {10.48550/arXiv.2602.10701},
     publisher = {arXiv},
     author = {Faas, Cedric and Uth, Richard and Sterz, Sarah and Langer, Markus and Feit, Anna Maria},
     month = feb,
     year = {2026},
   }

2024

1. 

   Give Me a Choice: The Consequences of Restricting Choices Through AI-Support for Perceived Autonomy, Motivational Variables, and Decision Performance

   Cedric Faas, Richard Bergs, Sarah Sterz, Markus Langer, and Anna Maria Feit

   Feb 2024

   arXiv Bib PDF

   @misc{faas2024choiceconsequencesrestrictingchoices,
     title = {Give Me a Choice: The Consequences of Restricting Choices Through AI-Support for Perceived Autonomy, Motivational Variables, and Decision Performance},
     author = {Faas, Cedric and Bergs, Richard and Sterz, Sarah and Langer, Markus and Feit, Anna Maria},
     year = {2024},
     eprint = {2410.07728},
     archiveprefix = {arXiv},
     primaryclass = {cs.HC},
     url = {https://arxiv.org/abs/2410.07728},
   }