zurück

Expert Interviews on Uncertainty-Aware Explanations

Bachelorarbeit, Masterarbeit

Overview

Expert perspectives play a crucial role in understanding the real-world applicability of AI systems, particularly when it comes to communicating uncertainty. This thesis will involve conducting semi-structured interviews with experts (e.g., medical professionals, data scientists, or policy advisors) to explore their views on the design and use of uncertainty-aware explanations in healthcare AI systems.

The goal is to analyze how experts perceive uncertainty communication, identify practical challenges, and uncover opportunities for integrating uncertainty-aware explanations into healthcare workflows. Findings will contribute to the development of user-centered, ethically aligned AI systems.

Application

To apply, send your CV, transcript, and a statement of interest to . Strong communication skills and an interest in qualitative research methods are required. Prior experience with interview-based studies is a plus.

Literature

  • Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59-82.
  • O’Connor, C., & Joffe, H. (2020). Intercoder reliability in qualitative research: Debates and practical guidelines. International Journal of Qualitative Methods, 19, 1-13.
  • Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Sage Publications.
  • Kaplan, B., & Maxwell, J. A. (2005). Qualitative research methods for evaluating computer information systems. Evaluating the Organizational Impact of Healthcare Information Systems, 30-55.
  • Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101.
  • Hoffman, R. R., & Novak, T. P. (2018). Human-centered AI: The role of human-centered design research in the development of AI. Journal of Business Research, 100, 1-10