Kacper Sokol

Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence

2021 · arXiv (Cornell University)

Explainable artificial intelligence and interpretable machine learning are research domains growing in importance. Yet, the underlying concepts remain somewhat elusive and lack generally agreed definitions. While recent inspiration from social sciences has refocused the work …

What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components

2022 · arXiv (Cornell University)

Explainability techniques for data-driven predictive models based on artificial intelligence and machine learning algorithms allow us to better understand the operation of such systems and help to hold them accountable. New transparency approaches are developed …