Computer Vision and Xai - Sara Tähtinen | PyData Global 2021

Computer Vision and Xai: Explaining a Single Prediction With Visualisations and Examples Speaker: Sara Tähtinen Summary Explainable AI is a broad field of study that aims to explain the results of an AI system in an easy, human readable way. In this talk I will focus on methods that aim to explain one image prediction at the time. First I will discuss visualisations techniques and then using examples to explain the model’s result. I will also show results of my own experiments to support the theory. Description Assume you have a model that labels images. You show the model a picture of a cat but the model claims that it is a dog. The result is quite surprising and you are left to wonder: why did the model misclassify this image? What made it so confused that it thought that the cat is actually a dog? This is just one example what could happen when complex AI models are used in practise. There are many cases where you must be sure the model works correctly but you are not