London Information Retrieval Meetup
Free evening meetup aimed to Information Retrieval passionates and professionals who are curious to explore and discuss the latest trends in the field.
Location: London (online)
Date: 30th March 2021
Explainability for Learning to Rank
In the last few years, Artificial Intelligence applications have become more and more sophisticated and often operate like algorithmic “black boxes” for decision-making. Due to this fact, some questions naturally arise when working with these models: why should we trust a certain decision taken by these algorithms? Why and how was this prediction made? Which variables mostly influenced the prediction? The most crucial challenge with complex machine learning models is therefore their interpretability and explainability. This talk aims to illustrate an overview of the most popular explainability techniques and their application in Learning to Rank. In particular, we will examine in depth a powerful library called SHAP with both theoretical and practical insights; we will talk about its amazing tools to give an explanation of the model behaviour, especially how each feature impacts the model’s output, and we will explain to you how to interpret the results in a Learning to Rank scenario.