DaSSWeb – Data Science and Statistics Webinar
Tuesday, 5 November, 14:30 (GMT)
Speaker
Peter Flach
School of Computer Science, University of Bristol, UK
Title
Explainable Artificial Intelligence, Explained
Zoom link
Abstract
Explainable Artificial Intelligence (XAI for short) aims at giving insight in the behaviour of AI models in general
and machine learning models in particular. In this talk I will give an overview of this growing field,
using some recent results from my group as examples. These include explainability for time series (LIMEsegment);
actionable counterfactuals (FACE); explainability fact sheets; as well as the fat-forensics.org toolkit for evaluating
Fairness, Accountability and Transparency of AI systems. Finally, I will discuss the importance of properly
treating probabilities in feature attribution methods such as LIME and SHAP through log-linear models,
and extensions to multi-class settings.
More information at
DaSSWeb-Peter-Flach-5Nov2024.pdf