Naeem Ullah, Javed Ali Khan, Ivanoe De Falco, Giovanna Sannino
{"title":"Explainable Artificial Intelligence: Importance, Use Domains, Stages, Output Shapes, and Challenges","authors":"Naeem Ullah, Javed Ali Khan, Ivanoe De Falco, Giovanna Sannino","doi":"10.1145/3705724","DOIUrl":null,"url":null,"abstract":"There is an urgent need in many application areas for eXplainable ArtificiaI Intelligence (XAI) approaches to boost people’s confidence and trust in Artificial Intelligence methods. Current works concentrate on specific aspects of XAI and avoid a comprehensive perspective. This study undertakes a systematic survey of importance, approaches, methods, and application domains to address this gap and provide a comprehensive understanding of the XAI domain. Applying the Systematic Literature Review approach has resulted in finding and discussing 155 papers, allowing a wide discussion on the strengths, limitations, and challenges of XAI methods and future research directions.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"27 1","pages":""},"PeriodicalIF":23.8000,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Computing Surveys","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3705724","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
There is an urgent need in many application areas for eXplainable ArtificiaI Intelligence (XAI) approaches to boost people’s confidence and trust in Artificial Intelligence methods. Current works concentrate on specific aspects of XAI and avoid a comprehensive perspective. This study undertakes a systematic survey of importance, approaches, methods, and application domains to address this gap and provide a comprehensive understanding of the XAI domain. Applying the Systematic Literature Review approach has resulted in finding and discussing 155 papers, allowing a wide discussion on the strengths, limitations, and challenges of XAI methods and future research directions.
期刊介绍:
ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods.
ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.