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Over the last two years, The Alan Turing Institute and the InformationCommissioner's Office (ICO) have been working together to discover ways totackle the difficult issues surrounding explainable AI. The ultimate product ofthis joint endeavour, Explaining decisions made with AI, published in May 2020,is the most comprehensive practical guidance on AI explanation producedanywhere to date. We have put together this workbook to help support the uptakeof that guidance. The goal of the workbook is to summarise some of main themesfrom Explaining decisions made with AI and then to provide the materials for aworkshop exercise that has been built around a use case created to help yougain a flavour of how to put the guidance into practice. In the first threesections, we run through the basics of Explaining decisions made with AI. Weprovide a precis of the four principles of AI explainability, the typology ofAI explanations, and the tasks involved in the explanation-aware design,development, and use of AI/ML systems. We then provide some reflectionquestions, which are intended to be a launching pad for group discussion, and astarting point for the case-study-based exercise that we have included asAppendix B. In Appendix A, we go into more detailed suggestions about how toorganise the workshop. These recommendations are based on two workshops we hadthe privilege of co-hosting with our colleagues from the ICO and ManchesterMetropolitan University in January 2021. The participants of these workshopscame from both the private and public sectors, and we are extremely grateful tothem for their energy, enthusiasm, and tremendous insight. This workbook wouldsimply not exist without the commitment and keenness of all our collaboratorsand workshop participants.

Explaining decisions made with AI: A workbook (Use case 1: AI-assisted recruitment tool)