Trust in automated medical imaging technology

Centre for health informatics

Research stream

Precision Health

Project members

Professor Shlomo Berkovsky – Precision Health
Dr Kiran Ijaz – Research Fellow
Dr David Lyell - Postdoctoral Researcher
Dr Hazel Jenkins - Lecturer

Project contact

Dr Kirn Ijaz
E: kiran.ijaz@mq.edu.au

Project main description

Recent years have seen growth in automation technology applications in emergency healthcare, monitoring patients, medical billing systems, and computer-aided detection to name a few. While automation technology has benefits that can save effort and cost in health care processes. There are also associated risks to not trust when required or even over trusting the system. Trust in automation is a complex construct and interactions of many factors such as system accuracy, task complexity, perceived risk, operator accuracy, fatigue, state learning etc. impact automation use. System accuracy directly impacts human’s trust in the machine. There is little known about trust and reliance in automated medical imaging technology as a decision aid. This project explores human trust, reliance and performance dynamics while changing the systems’ accuracy.

Objective

To investigate building and maintaining human-machine trust and reliance using automated medical imaging technology as a decision aid.

Research Questions

Will radiologists trust an automated machine with demonstrated accuracy?
Will radiologists trust decrease when the automated machine’s accuracy decreases?
After exposure to an inaccurate system, does trust recover when exposed to perfectly accurate system?
How does system’s accuracy relate to participant’s task accuracy, reliance and performance?

References

1. Yu, K., Berkovsky, S., Taib, R., Zhou, J., & Chen, F. (2019). Do I trust my machine teammate? International Conference on Intelligent User Interfaces, Proceedings IUI, 460–468. https://doi.org/10.1145/3301275.3302277
2. Yu, K., Conway, D., Berkovsky, S., Zhou, J., Taib, R., & Chen, F. (2017). User trust dynamics: An investigation driven by differences in system performance. International Conference on Intelligent User Interfaces, Proceedings IUI, 307–317. https://doi.org/10.1145/3025171.3025219
3. Yu, K., Taib, R., Berkovsky, S., Zhou, J., Conway, D., & Chen, F. (2016). Trust and Reliance based on system accuracy. UMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization, 223–227. https://doi.org/10.1145/2930238.2930290

Project sponsors

NHMRC Centre of Research Excellence in Digital Health

Project status

Current

Centres related to this project

Centre for Health Informatics