Increasing automation in the healthcare sector calls for a Hybrid Intelligence (HI) approach to closely study and design the collaboration of humans and autonomous machines. Ensuring that medical HI systems' decision-making is ethical is key. The use of Team Design Patterns (TDPs) can advance this goal by describing successful and reusable configurations of design problems in which decisions have a moral component and facilitating communication in multidisciplinary teams designing HI systems. For this research, TDPs were developed describing a set of solutions for a design problem in a medical HI system: mitigating harmful biases in machine learning algorithms. The Socio-Cognitive Engineering (SCE) methodology was employed, integrating operational demands, human factors knowledge, and a technological analysis into a set of TDPs. A survey was created to assess the usability of the patterns with regards to their understandability, effectiveness, and generalizability. Results showed that TDPs are a useful method to unambiguously describe solutions for diverse HI design problems with a moral component on varying abstraction levels, usable by a heterogeneous group of multidisciplinary researchers. Additionally, results indicated that the SCE approach and the developed questionnaire are suitable methods for creating and assessing TDPs.
|Title of host publication||AAAI-MAKE 2021 Combining Machine Learning and Knowledge Engineering|
|Subtitle of host publication||Proceedings of the AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021) Stanford University, Palo Alto, California, USA, March 22-24, 2021|
|Editors||Andreas Martin, Knut Hinkelmann, Hans-Georg Fill, Aurona Gerber, Doug Lenat, Reinhard Stolle, Frank van Harmelen|
|Number of pages||12|
|Publication status||Published - 10 Apr 2021|
|Event||2021 AAAI Spring Symposium on Combining Machine Learning and Knowledge Engineering, AAAI-MAKE 2021 - Palo Alto, United States|
Duration: 22 Mar 2021 → 24 Mar 2021
|Name||CEUR Workshop Proceedings|
|Publisher||CEUR Workshop Proceedings|
|Conference||2021 AAAI Spring Symposium on Combining Machine Learning and Knowledge Engineering, AAAI-MAKE 2021|
|Period||22/03/21 → 24/03/21|
Bibliographical noteFunding Information:
The study was part of the TNO FATE-project; we thank the TNO researchers for their contribution. It was further supported by the Hybrid Intelligence Center, funded by the Dutch Ministry of Education, Culture and Science (through NWO).
© 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org)
Copyright 2021 Elsevier B.V., All rights reserved.
- Bias mitigation
- Hybrid intelligence
- Moral decision-making
- Socio-cognitive engineering
- Team design patterns
- Value-sensitive design