Explainable Artificial Intelligence (XAI)

IF 1.5 4区管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information Technology and Libraries Pub Date : 2022-06-15 DOI:10.6017/ital.v41i2.14683

M. Ridley

引用次数: 707

Abstract

The field of explainable artificial intelligence (XAI) advances techniques, processes, and strategies that provide explanations for the predictions, recommendations, and decisions of opaque and complex machine learning systems. Increasingly academic libraries are providing library users with systems, services, and collections created and delivered by machine learning. Academic libraries should adopt XAI as a tool set to verify and validate these resources, and advocate for public policy regarding XAI that serves libraries, the academy, and the public interest.

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可解释人工智能（XAI）

可解释人工智能（XAI）领域进步了为不透明和复杂的机器学习系统的预测、建议和决策提供解释的技术、过程和策略。越来越多的学术图书馆为图书馆用户提供通过机器学习创建和提供的系统、服务和收藏。学术图书馆应采用XAI作为验证和验证这些资源的工具集，并倡导有关XAI的公共政策，为图书馆、学院和公众利益服务。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Information Technology and Libraries 管理科学-计算机：信息系统

CiteScore

2.90

自引率

5.60%

发文量

审稿时长

1 months

期刊介绍： Information Technology and Libraries publishes original material related to all aspects of information technology in all types of libraries. Topic areas include, but are not limited to, library automation, digital libraries, metadata, identity management, distributed systems and networks, computer security, intellectual property rights, technical standards, geographic information systems, desktop applications, information discovery tools, web-scale library services, cloud computing, digital preservation, data curation, virtualization, search-engine optimization, emerging technologies, social networking, open data, the semantic web, mobile services and applications, usability, universal access to technology, library consortia, vendor relations, and digital humanities.