Working in contexts for which transparency is important

Author:

Bunn Jenny

Abstract

Purpose This paper aims to introduce the topic of explainable artificial intelligence (XAI) and reports on the outcomes of an interdisciplinary workshop exploring it. It reflects on XAI through the frame and concerns of the recordkeeping profession. Design/methodology/approach This paper takes a reflective approach. The origins of XAI are outlined as a way of exploring how it can be viewed and how it is currently taking shape. The workshop and its outcomes are briefly described and reflections on the process of investigating and taking part in conversations about XAI are offered. Findings The article reinforces the value of undertaking interdisciplinary and exploratory conversations with others. It offers new perspectives on XAI and suggests ways in which recordkeeping can productively engage with it, as both a disruptive force on its thinking and a set of newly emerging record forms to be created and managed. Originality/value The value of this paper comes from the way in which the introduction it provides will allow recordkeepers to gain a sense of what XAI is and the different ways in which they are both already engaging and can continue to engage with it.

Publisher

Emerald

Subject

Library and Information Sciences,Management Information Systems

Reference31 articles.

1. Trends and trajectories for explainable, accountable and intelligible systems: an HCI research agenda,2018

2. Annual Conference on Neural Information Processing Systems (2016), “Interpretable ML for complex systems NIPS 2016”, available at https://sites.google.com/site/nips2016interpretml/ (accessed 20 August 2019).

3. Association of Computing Machinery (2017), “Statement on algorithmic transparency and accountability”, available at: www.acm.org/binaries/content/assets/public-policy/2017_usacm_statement_algorithms.pdf (accessed 20 August 2019).

4. Bunn, J. (2019a), “Workshop on human-centered explainable artificial intelligence”, available at https://blogs.ucl.ac.uk/hexai/ (accessed 20 August 2019).

5. Bunn, J. (2019b), “Participants”, available at https://blogs.ucl.ac.uk/hexai/participants (accessed 20 August 2019).

Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Explainable Artificial Intelligence as a Cybersecurity Aid;Advances in Explainable AI Applications for Smart Cities;2024-01-18

2. AI-Generated Images as an Emergent Record Format;2023 IEEE International Conference on Big Data (BigData);2023-12-15

3. AI-Powered Archives: Revolutionizing Information Access for the Future;2023 IEEE International Conference on Big Data (BigData);2023-12-15

4. Positioning Paradata: A Conceptual Frame for AI Processual Documentation in Archives and Recordkeeping Contexts;Journal on Computing and Cultural Heritage;2023-11-16

5. Algorithmic futures: the intersection of algorithms and evidentiary work;Information, Communication & Society;2023-09-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3