| Abstract |
This paper presents a five-step systematic method in the development of an explainable AI (XAI) system, to (i) understand specific explanation requirements, (ii) assess existing explanation capabilities and (iii) steer future research and development in this area. A case study is discussed whereby the method was developed and applied within an industrial context. This paper is a summary of research originally published at the XAI workshop at IJCAI, 2019. |
| Authors |
- Mark Hall (Airbus)
- Dan Harborne (Cardiff)
- Richard Tomsett (IBM UK)
- Vedran Galetic (Airbus)
- Santiago Quintana (Airbus)
- Alistair Nottle (Airbus)
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| Date |
Sep-2019 |
| Venue |
Annual Fall Meeting of the DAIS ITA, 2019 |
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| Variants |
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