  Over the last two years, The Alan Turing Institute and the Information
Commissioner's Office (ICO) have been working together to discover ways to
tackle the difficult issues surrounding explainable AI. The ultimate product of
this joint endeavour, Explaining decisions made with AI, published in May 2020,
is the most comprehensive practical guidance on AI explanation produced
anywhere to date. We have put together this workbook to help support the uptake
of that guidance. The goal of the workbook is to summarise some of main themes
from Explaining decisions made with AI and then to provide the materials for a
workshop exercise that has been built around a use case created to help you
gain a flavour of how to put the guidance into practice. In the first three
sections, we run through the basics of Explaining decisions made with AI. We
provide a precis of the four principles of AI explainability, the typology of
AI explanations, and the tasks involved in the explanation-aware design,
development, and use of AI/ML systems. We then provide some reflection
questions, which are intended to be a launching pad for group discussion, and a
starting point for the case-study-based exercise that we have included as
Appendix B. In Appendix A, we go into more detailed suggestions about how to
organise the workshop. These recommendations are based on two workshops we had
the privilege of co-hosting with our colleagues from the ICO and Manchester
Metropolitan University in January 2021. The participants of these workshops
came from both the private and public sectors, and we are extremely grateful to
them for their energy, enthusiasm, and tremendous insight. This workbook would
simply not exist without the commitment and keenness of all our collaborators
and workshop participants.
