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. I...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
An important subdomain in research on Human-Artificial Intelligence interaction is Explainable AI (X...
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of e...
Over the last two years, The Alan Turing Institute and the Information Commissioner’s Office (ICO) h...
Governments look at explainable artificial intelligence's (XAI) potential to tackle the criticisms o...
Explainability is assumed to be a key factor for the adoption of Artificial Intelligence systems in ...
As artificial intelligence (AI) systems increasingly make impactful decisions in the workplace, issu...
eXplainable AI focuses on generating explanations for the output of an AI algorithm to a user, usual...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Artificial Intelligence systems are spreading to multiple applications and they are used by a more d...
The most effective Artificial Intelligence (AI) systems exploit complex machine learning models to f...
Explainability in Artificial Intelligence (AI) has been revived as a topic of active research by the...
Purpose: Inscrutable machine learning (ML) models are part of increasingly many information systems....
The requirements of transparency or explainability draw considerable attention in AI ethics. Still, ...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
An important subdomain in research on Human-Artificial Intelligence interaction is Explainable AI (X...
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of e...
Over the last two years, The Alan Turing Institute and the Information Commissioner’s Office (ICO) h...
Governments look at explainable artificial intelligence's (XAI) potential to tackle the criticisms o...
Explainability is assumed to be a key factor for the adoption of Artificial Intelligence systems in ...
As artificial intelligence (AI) systems increasingly make impactful decisions in the workplace, issu...
eXplainable AI focuses on generating explanations for the output of an AI algorithm to a user, usual...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Artificial Intelligence systems are spreading to multiple applications and they are used by a more d...
The most effective Artificial Intelligence (AI) systems exploit complex machine learning models to f...
Explainability in Artificial Intelligence (AI) has been revived as a topic of active research by the...
Purpose: Inscrutable machine learning (ML) models are part of increasingly many information systems....
The requirements of transparency or explainability draw considerable attention in AI ethics. Still, ...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
An important subdomain in research on Human-Artificial Intelligence interaction is Explainable AI (X...
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of e...