DARPA's explainable AI (XAI) program: A retrospective The main objective of DiCE is to explain the predictions of ML-based systems that are used to inform decisions in societally critical domains such as finance, healthcare, education, and criminal justice. These techniques can help them write explanations of their models. arXiv preprint arXiv:2203.08813, 2022. Despite being studied actively, existing optimization-based methods often assume that the underlying machine-learning model is differentiable and treat categorical attributes as continuous ones, which restricts their real-world applications when … In this chapter and section, we will be exploring AI explanations in a unique way. August 2021. Counterfactual Explanations in Explainable AI: A Tutorial. Counterfactuals about what could have happened are increasingly used in an array of Artificial Intelligence (AI) applications, and especially in explainable AI (XAI). Explainable Abstract. Denis Rothman (2021) … 36. Coherence is an essential property of explanations but is not yet addressed sufficiently by existing XAI methods. Source: Gunning, D. (2017). This paper aims to provide an overview of the research studies, presented since 2017, focusing on ML and DL developed methods for disaster management. Browse Library Sign In Start Free Trial. Findings about the nature of the counterfactuals that humans create are a helpful guide to maximize the effectiveness ofcounterfactual use in AI. In these domains, it is important to provide … Data analysts and data scientists want to learn about AI tools and techniques that are easy to understand. Abstract Deep learning models have achieved high performance across different domains, such as medical decision-making, autonomous vehicles, decision support systems, among many others. Over the last few years we have seen a resurgence of interest in AI technologies from … ... How Duolingo Uses AI to Assess, Engage and Teach Better. Lime stands for Local interpretable model agnostic explanations. First, several features may be immutable and therefore inapplicable for recourse, e.g., number of past delinquencies. Let us train a state of the art AI! AI ‪Xiao-Hui Li‬ - ‪Google 学术搜索‬ enhancing, with XAI 41. Proceedings of the international Conference on Human Factors in Computing Systems.