Our research associate Tobias Huber presented two papers of the HCAI chair at the  Joint Conference on Artificial Intelligence (IJCAI) in Vienna. Both papers belong to the research area of Explainable Artificial Intelligence that aims to make the behavior of increasingly opaque AI methods understandable.
The paper „ Local and global explanations of agent behavior: Integrating strategy summaries with saliency maps“ compares local explanations, which analyze individual decisions of an agent, with global explanations, which shed light on the overall strategy of the agent.
The XAI Workshop paper „ Alterfactual Explanations – The Relevance of Irrelevance for Explaining AI Systems“ proposes a novel explanation method to help identify irrelevant information for a given AI decision.