Stumpf, Simone

XAI—Explainable artificial intelligence

Gunning, D., Stefik, M., Choi, J., Miller, T., Stumpf, S., & Yang, G.-Z. (2019) · Science Robotics

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 2,053

Principles of Explanatory Debugging to Personalize Interactive Machine Learning

Kulesza, T., Burnett, M., Wong, W.-K., & Stumpf, S. (2015) · Proceedings of the 20th International Conference on Intelligent User Interfaces

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 576

The Role of Explanations on Trust and Reliance in Clinical Decision Support Systems

Bussone, A., Stumpf, S., & O'Sullivan, D. (2015) · 2015 International Conference on Healthcare Informatics

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 441

Too much, too little, or just right? Ways explanations impact end users' mental models

Kulesza, T., Stumpf, S., Burnett, M., Yang, S., Kwan, I., & Wong, W.-K. (2013) · 2013 IEEE Symposium on Visual Languages and Human Centric Computing

Explainable Artificial Intelligence (XAI)Usability and User Interface Design

Cited by 388

Explainable AI: The New 42?

Goebel, R., Chander, A., Holzinger, K., Lecue, F., Akata, Z., Stumpf, S., Kieseberg, P., & Holzinger, A. (2018) · Lecture Notes in Computer Science

Explainable Artificial Intelligence (XAI)Logic, Reasoning, and Knowledge

Cited by 259

Tell me more?: the effects of mental model soundness on personalizing an intelligent agent

Kulesza, T., Stumpf, S., Burnett, M., & Kwan, I. (2012) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Recommender Systems and TechniquesUsability and User Interface Design

Cited by 225

Interacting meaningfully with machine learning systems: Three experiments

Stumpf, S., Rajaram, V., Li, L., Wong, W.-K., Burnett, M., Dietterich, T., Sullivan, E., & Herlocker, J. (2009) · International Journal of Human-Computer Studies

Usability and User Interface DesignExplainable Artificial Intelligence (XAI)

Cited by 184

Fixing the program my computer learned: barriers for end users, challenges for the machine

Kulesza, T., Wong, W.-K., Stumpf, S., Perona, S., White, R., Burnett, M. M., Oberst, I., & Ko, A. J. (2009) · Proceedings of the 14th international conference on Intelligent user interfaces

Software Testing and Debugging TechniquesUsability and User Interface Design

Cited by 83

Toward involving end-users in interactive human-in-the-loop AI fairness

Nakao, Y., Stumpf, S., Ahmed, S., Naseer, A., & Strappelli, L. (2022) · ACM Transactions on Interactive Intelligent Systems

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 69

Interdependence in Action: People with Visual Impairments and their Guides Co-constituting Common Spaces

Vincenzi, B., Taylor, A. S., & Stumpf, S. (2021) · Proceedings of the ACM on Human-Computer Interaction

Assistive Technology in Communication and MobilityDigital Accessibility for Disabilities

Cited by 48

Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors

Theodorou, L., Massiceti, D., Zintgraf, L., Stumpf, S., Morrison, C., Cutrell, E., Harris, M. T., & Hofmann, K. (2021) · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility

Assistive Technology in Communication and MobilityDigital Accessibility for Disabilities

Cited by 42

Detecting and correcting user activity switches: algorithms and interfaces

Shen, J., Irvine, J., Bao, X., Goodman, M., Kolibaba, S., Tran, A., Carl, F., Kirschner, B., Stumpf, S., & Dietterich, T. G. (2009) · Proceedings of the 14th international conference on Intelligent user interfaces

Context-Aware Activity Recognition SystemsPersonal Information Management and User Behavior

Cited by 37

ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition

Massiceti, D., Zintgraf, L., Bronskill, J., Theodorou, L., Harris, M. T., Cutrell, E., Morrison, C., Hofmann, K., & Stumpf, S. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 33

Workshop on Trust and Reliance in AI-Human Teams (TRAIT)

Bansal, G., Buçinca, Z., Holstein, K., Hullman, J., Smith-Renner, A. M., Stumpf, S., & Wu, S. (2023) · Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Human-Automation Interaction and SafetySocial Robot Interaction and HRI

Cited by 8

End-User Development: 9th International Symposium, IS-EUD 2023, Cagliari, Italy, June 6–8, 2023, Proceedings

Spano, L. D., Schmidt, A., Santoro, C., & Stumpf, S. (2023) · Lecture Notes in Computer Science

Spreadsheets and End-User ComputingUsability and User Interface Design

Cited by 4

Evaluating a digital mental health intervention for people with Parkinson's (PACT): acceptability and feasibility randomised controlled trial.

Pinto, C., Norton, S., Cubi-Molla, P., Hurt, C., Chowdhury, S., Dooley, N., Safwi, A., Brown, J., Volpato, R., Stumpf, S., et al. (2025) · Aging & Mental Health

Digital Mental Health InterventionsMindfulness and Compassion Interventions

Cited by 2

Human-in-the-loop Fairness: Integrating Stakeholder Feedback to Incorporate Fairness Perspectives in Responsible AI

Taka, E., Nakao, Y., Sonoda, R., Yokota, T., Luo, L., & Stumpf, S. (2023) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 0