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

TL;DR

This paper provides a practical workbook to help implement AI explainability principles, using a case study on AI-assisted recruitment to facilitate understanding and application of explainable AI guidance.

Contribution

It offers a structured, workshop-based approach to applying comprehensive AI explanation guidance through a real-world use case in recruitment.

Findings

Workshop exercises enhance understanding of AI explainability principles

Case study demonstrates practical application of explanation guidance

Guidance supports better implementation of explainable AI in real-world scenarios

Abstract

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.