AI-driven disinformation: a framework for organizational preparation and response

IF 3.1 Q1 COMMUNICATION
Elise Karinshak, Yan Jin
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引用次数: 0

Abstract

PurposeDisinformation, false information designed with the intention to mislead, can significantly damage organizational operation and reputation, interfering with communication and relationship management in a wide breadth of risk and crisis contexts. Modern digital platforms and emerging technologies, including artificial intelligence (AI), introduce novel risks in crisis management (Guthrie and Rich, 2022). Disinformation literature in security and computer science has assessed how previously introduced technologies have affected disinformation, demanding a systematic and coordinated approach for sustainable counter-disinformation efforts. However, there is a lack of theory-driven, evidence-based research and practice in public relations that advises how organizations can effectively and proactively manage risks and crises driven by AI (Guthrie and Rich, 2022).Design/methodology/approachAs a first step in closing this research-practice gap, the authors first synthesize theoretical and technical literature characterizing the effects of AI on disinformation. Upon this review, the authors propose a conceptual framework for disinformation response in the corporate sector that assesses (1) technologies affecting disinformation attacks and counterattacks and (2) how organizations can proactively prepare and equip communication teams to better protect businesses and stakeholders.FindingsThis research illustrates that future disinformation response efforts will not be able to rely solely on detection strategies, as AI-created content quality becomes more and more convincing (and ultimately, indistinguishable), and that future disinformation management efforts will need to rely on content influence rather than volume (due to emerging capabilities for automated production of disinformation). Built upon these fundamental, literature-driven characteristics, the framework provides organizations actor-level and content-level perspectives for influence and discusses their implications for disinformation management.Originality/valueThis research provides a theoretical basis and practitioner insights by anticipating how AI technologies will impact corporate disinformation attacks and outlining how companies can respond. The proposed framework provides a theory-driven, practical approach for effective, proactive disinformation management systems with the capacity and agility to detect risks and mitigate crises driven by evolving AI technologies. Together, this framework and the discussed strategies offer great value to forward-looking disinformation management efforts. Subsequent research can build upon this framework as AI technologies are deployed in disinformation campaigns, and practitioners can leverage this framework in the development of counter-disinformation efforts.
人工智能驱动的虚假信息:组织准备和应对的框架
disinformation(虚假信息),旨在误导的虚假信息,可以严重损害组织的运作和声誉,在广泛的风险和危机环境中干扰沟通和关系管理。现代数字平台和新兴技术,包括人工智能(AI),在危机管理中引入了新的风险(Guthrie和Rich, 2022)。安全和计算机科学领域的虚假信息文献评估了以前引入的技术如何影响虚假信息,要求采用系统和协调的方法来开展可持续的反虚假信息工作。然而,公共关系领域缺乏理论驱动的、基于证据的研究和实践,这些研究和实践建议组织如何有效和主动地管理由人工智能驱动的风险和危机(Guthrie和Rich, 2022)。设计/方法/方法作为缩小研究与实践差距的第一步,作者首先综合了描述人工智能对虚假信息影响的理论和技术文献。在此基础上,作者提出了一个企业部门虚假信息响应的概念框架,该框架评估了(1)影响虚假信息攻击和反击的技术;(2)组织如何积极准备和装备沟通团队,以更好地保护企业和利益相关者。这项研究表明,未来的虚假信息响应工作将不能仅仅依赖于检测策略,因为人工智能创建的内容质量变得越来越有说服力(最终,难以区分),未来的虚假信息管理工作将需要依赖于内容影响而不是数量(由于自动化生产虚假信息的新能力)。基于这些基本的、文献驱动的特征,该框架为组织提供了行为者层面和内容层面的影响视角,并讨论了它们对虚假信息管理的影响。原创性/价值本研究通过预测人工智能技术将如何影响企业虚假信息攻击,并概述企业如何应对,提供了理论基础和从业者见解。拟议的框架为有效、主动的虚假信息管理系统提供了一种理论驱动的实用方法,该系统具有检测风险和缓解不断发展的人工智能技术驱动的危机的能力和敏捷性。总之,这个框架和所讨论的策略为前瞻性的虚假信息管理工作提供了巨大的价值。随后的研究可以建立在这个框架上,因为人工智能技术被部署在虚假信息活动中,从业者可以利用这个框架来发展反虚假信息的努力。
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
CiteScore
5.40
自引率
6.50%
发文量
29
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