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Explainable Artificial Intelligence (XAI) is an emerging area of research in the field of Artificial Intelligence (AI). XAI can explain how AI obtained a particular solution (e.g., classification or object detection) and can also answer…

机器学习 · 计算机科学 2021-07-16 Prashant Gohel , Priyanka Singh , Manoranjan Mohanty

The field of "explainable artificial intelligence" (XAI) seemingly addresses the desire that decisions of machine learning systems should be human-understandable. However, in its current state, XAI itself needs scrutiny. Popular methods…

There has recently been a surge of work in explanatory artificial intelligence (XAI). This research area tackles the important problem that complex machines and algorithms often cannot provide insights into their behavior and thought…

人工智能 · 计算机科学 2019-02-05 Leilani H. Gilpin , David Bau , Ben Z. Yuan , Ayesha Bajwa , Michael Specter , Lalana Kagal

In the last years, Artificial Intelligence (AI) has achieved a notable momentum that may deliver the best of expectations over many application sectors across the field. For this to occur, the entire community stands in front of the barrier…

The demand for Explainable AI (XAI) has triggered an explosion of methods, producing a landscape so fragmented that we now rely on surveys of surveys. Yet, fundamental challenges persist: conflicting metrics, failed sanity checks, and…

机器学习 · 计算机科学 2026-03-31 Amir-Hossein Karimi

Explainable AI (XAI) is paramount in industry-grade AI; however existing methods fail to address this necessity, in part due to a lack of standardisation of explainability methods. The purpose of this paper is to offer a perspective on the…

机器学习 · 计算机科学 2020-10-26 Othman Benchekroun , Adel Rahimi , Qini Zhang , Tetiana Kodliuk

The past decade has seen significant progress in artificial intelligence (AI), which has resulted in algorithms being adopted for resolving a variety of problems. However, this success has been met by increasing model complexity and…

机器学习 · 计算机科学 2021-11-15 Waddah Saeed , Christian Omlin

Explainable AI (XAI) has been investigated for decades and, together with AI itself, has witnessed unprecedented growth in recent years. Among various approaches to XAI, argumentative models have been advocated in both the AI and social…

人工智能 · 计算机科学 2021-05-25 Kristijonas Čyras , Antonio Rago , Emanuele Albini , Pietro Baroni , Francesca Toni

Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few years. This is due to the widespread application of machine learning, particularly deep learning, that has led to the development of highly…

人工智能 · 计算机科学 2020-10-13 Giulia Vilone , Luca Longo

In this work, we report the practical and theoretical aspects of Explainable AI (XAI) identified in some fundamental literature. Although there is a vast body of work on representing the XAI backgrounds, most of the corpuses pinpoint a…

人工智能 · 计算机科学 2020-12-18 Nazanin Fouladgar , Kary Främling

As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research…

Explainable Artificial Intelligence (XAI) is an emerging research field bringing transparency to highly complex and opaque machine learning (ML) models. Despite the development of a multitude of methods to explain the decisions of black-box…

机器学习 · 计算机科学 2022-03-16 Leander Weber , Sebastian Lapuschkin , Alexander Binder , Wojciech Samek

Artificial intelligence models encounter significant challenges due to their black-box nature, particularly in safety-critical domains such as healthcare, finance, and autonomous vehicles. Explainable Artificial Intelligence (XAI) addresses…

人工智能 · 计算机科学 2025-03-14 Melkamu Mersha , Khang Lam , Joseph Wood , Ali AlShami , Jugal Kalita

The rapidly advancing domain of Explainable Artificial Intelligence (XAI) has sparked significant interests in developing techniques to make AI systems more transparent and understandable. Nevertheless, in real-world contexts, the methods…

人工智能 · 计算机科学 2023-09-08 Yulu Pi

Within the field of Requirements Engineering (RE), the increasing significance of Explainable Artificial Intelligence (XAI) in aligning AI-supported systems with user needs, societal expectations, and regulatory standards has garnered…

人工智能 · 计算机科学 2023-07-27 Timo Speith , Markus Langer

Recent years have seen important advances in the quality of state-of-the-art models, but this has come at the expense of models becoming less interpretable. This survey presents an overview of the current state of Explainable AI (XAI),…

计算与语言 · 计算机科学 2025-04-16 Marina Danilevsky , Kun Qian , Ranit Aharonov , Yannis Katsis , Ban Kawas , Prithviraj Sen

Explainable AI (XAI) research has been booming, but the question "$\textbf{To whom}$ are we making AI explainable?" is yet to gain sufficient attention. Not much of XAI is comprehensible to non-AI experts, who nonetheless, are the primary…

人机交互 · 计算机科学 2021-12-03 Helen Jiang , Erwen Senge

EXplainable Artificial Intelligence (XAI) is a vibrant research topic in the artificial intelligence community, with growing interest across methods and domains. Much has been written about the subject, yet XAI still lacks shared…

人工智能 · 计算机科学 2023-06-16 Matteo Rizzo , Alberto Veneri , Andrea Albarelli , Claudio Lucchese , Marco Nobile , Cristina Conati

Artificial intelligence (AI) has been clearly established as a technology with the potential to revolutionize fields from healthcare to finance - if developed and deployed responsibly. This is the topic of responsible AI, which emphasizes…

人工智能 · 计算机科学 2023-12-05 Stephanie Baker , Wei Xiang

In this survey paper, we deep dive into the field of Explainable Artificial Intelligence (XAI). After introducing the scope of this paper, we start by discussing what an "explanation" really is. We then move on to discuss some of the…

人工智能 · 计算机科学 2023-06-06 Clive Gomes , Lalitha Natraj , Shijun Liu , Anushka Datta
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