DSM专刊征稿 | 面向智能社会5.0的可解释性动态数据驱动系统
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DSM专刊征稿
Call for Papers on Special Issue:
Explainable dynamic data-driven systems for Smart Society 5.0
面向智能社会5.0的可解释性动态数据驱动系统
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Submission due:
15 Feb. 2023
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专刊介绍
The first 20 years of the new millennium have been overwhelmed by the global information and communication technologies (ICT) tsunami. The continuous evolution of ICT has had a substantial impact on people, pushing them to live in a society that daily interfaces with intelligent systems. This has led to the concept of Smart Society 5.0, a term that describes the ideal shape for a future society in which intelligent systems, exploiting technological platforms to their full potential, are able to process huge amounts of data and analyses complex scenarios. In this future, people will be constantly supported by advanced tools within interconnected societies that are driven by digital transformation, supported by artificial intelligence (AI). However, these systems are often considered unreliable as they hide the underlying decision-making processes. The explainable AI paradigm aims to reduce the harmful implications caused by the opacity of these intelligent systems, investigating methodologies to ensure principles of fairness, responsibility and transparency.
This special issue will feature high-quality scientific contributions addressing novel aspects of intelligent systems that significantly improve the quality of people’s lives and their confidence in the decisions provided by such systems.
征稿范围
包括(但不限于)下列议题:
Argumentation theory for explainable AI
Decision model visualization tools
Designing new explanation styles
Ethics in explainable AI
Evaluations of decision-making metrics and processes
Evaluations of the transparency and interpretability of AI Systems
Explainable AI in risk management
Explainable and responsible AI systems for financial risk management
Explainable data mining and data profiling
Explainable decision-making processes
Explainable human-in-the-loop, dynamic, data-driven systems
Fairness and bias auditing
Human-machine interaction for explainable AI
Industry 4.0/5.0 systems
Information system management
Internet of Things (IoT)-based systems
Interpretable and transparent machine learning models
Monitoring and understanding system behavior
Natural language generation for explainable AI
Privacy by design approaches for human data
Privacy-preserving explanations
Property risk assessment using explainable AI
Successful applications of interpretable AI systems
Technical aspects of algorithms for explanation
Theoretical aspects of explanation and interpretability
投稿须知
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Please read the Guide for Authors before submitting;
All articles should be submitted online;
please select VSI: Explainable dynamic data-driven systems on submission.
客座主编
Dr. Gaetano Cimino, Department of Computer Science, University of Salerno, Italy.
Email: gcimino@unisa.it
Dr. Stefano Cirillo, Department of Computer Science, University of Salerno, Italy.
Email: scirillo@unisa.it
Dr. Aftab Alam, Department of Management Sciences, Abasyn University Peshawar, Pakistan.
Email: aftab.alam@abasyn.edu.pk
For further enquiries, please email dsm@xjtu.edu.cn, and the editing team will respond promptly.
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DSM
Data Science and Management(《数据科学与管理(英文)》,DSM)是一本由西安交通大学主办,西安交通大学管理学院、数学学院与期刊中心共同承办的开放获取英文学术期刊。期刊旨在推动数据科学研究及其在商业、工程、社会管理等领域的应用,聚焦数据科学与管理科学交叉领域,突出运用数据科学理论方法,解决数字化、网络化、智能化发展中的管理难题和经济社会转型发展中的关键问题。期刊由徐宗本院士担任主编,已入选FMS管理科学高质量国际期刊推荐列表,并已被Scopus、DOAJ数据库收录。
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期刊主页:
https://www.keaipublishing.com/en/journals/data-science-and-management/
投稿网址:
https://www.editorialmanager.com/dsm/default1.aspx
编辑 | 赵亚娟
校对 | 杨 越
审核 | 张 丛
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