Explaining decisions made with AI: A workbook (Use case 1: AI-assisted recruitment tool)
David Leslie, Morgan Briggs

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…
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Taxonomy
TopicsExplainable Artificial Intelligence (XAI) · Scientific Computing and Data Management · Artificial Intelligence in Healthcare and Education
