Title
The FATE System: FAir, Transparent and Explainable Decision making
Author
de Greeff, J.
de Boer, M.H.T.
Hillerström, F.H.J.
Bomhoff, F.W.
Jorritsma, W.
Neerinx, M.
Publication year
2021
Abstract
AI tools are becoming more commonly used in a variety of application domains. In this paper, we describe a system named FATE that combines state of the art AI tools. The goal of the FATE system is decision support with use of ongoing human-AI co-learning, explainable AI and fair, bias-free and secure usage of data. These topics are societally very relevant for the update of AI-based support systems, but the manner in which to bring these together into a working system is far from trivial. We describe the various functional components that comprise the system, share our experience with the set-up of such a system, explain how it can be used in a variety of use cases, taking into account multiple user roles. Finally, we reflect on this and provide an outlook for the continuation of this development.
Subject
FAIR AI
Hybrid AI
Explainable AI
Bias
Secure Learning
Knowledge Engineering
Co-learning
To reference this document use:
http://resolver.tudelft.nl/uuid:56112570-f78b-429f-a52f-656283162e16
TNO identifier
955837
Source
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.
Document type
conference paper