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CSET:人工智能和虚假信息运动的未来-Part 2(英文版)(90页).pdf

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1、 December 2021 AI and the Future of Disinformation Campaigns Part 2:A Threat Model CSET Policy Brief AUTHORS Katerina Sedova Christine McNeill Aurora Johnson Aditi Joshi Ido Wulkan Center for Security and Emerging Technology|1 Executive Summary The age of information enabled the age of disinformatio

2、n.Powered by the speed and volume of the internet,disinformation has emerged as an instrument of strategic competition and domestic political warfare.It is used by both state and non-state actors to shape public opinion,sow chaos,and erode societal trust.Artificial intelligence(AI),specifically mach

3、ine learning(ML),is poised to amplify disinformation campaignsinfluence operations that involve covert efforts to intentionally spread false or misleading information.1 In this series,we offer a systematic examination of how AI/ML technologies could enhance these operations.Part 1 of the series desc

4、ribed the stages and common techniques of disinformation campaigns.2 In this paper,we examine how AI/ML technologies can enhance specific disinformation techniques and how these technologies may exacerbate current trends and shape future campaigns.Our findings show that the use of AI in disinformati

5、on campaigns is not only plausible but already underway.Powered by computing,ML algorithms excel at harnessing data and finding patterns that are difficult for humans to observe.The data-rich environment of modern online existence creates a terrain ideally suited for ML techniques to precisely targe

6、t individuals.Language generation capabilities and the tools that enable deepfakes are already capable of manufacturing viral disinformation at scale and empowering digital impersonation.The same technologies,paired with human operators,may soon enable social bots to mimic human online behavior and

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本文主要探讨了人工智能(AI)和机器学习(ML)技术如何增强虚假信息(disinformation)运动。文章指出,AI/ML技术能够提高虚假信息运动的数据收集、情绪分析、目标受众细分、内容创作和深度伪造等各个阶段的能力。例如,自然语言处理(NLP)和生成(NLG)技术能够从丰富的在线环境中提取情感和情绪,从而进行更有效的社会工程。大型语言模型和生成对抗网络(GANs)能够大规模生成虚假信息,并模拟人类在线行为。深度伪造技术能够制作逼真的视频和音频。文章还指出,随着AI/ML技术的普及,虚假信息运动的风险可能会加剧,例如模糊了外国和国内影响行动的界限,将虚假信息的创建外包给私人公司,以及难以区分有害的虚假信息和受保护的言论。最后,文章提出了包括开发技术缓解措施、建立早期预警系统、建立跨平台集体防御网络、检查和遏制提供虚假信息服务的公司、整合威胁建模和红队过程、建立AI研究伦理原则、改革推荐算法和提高公众对ML驱动的虚假信息的认识等建议。
人工智能如何增强虚假信息运动? 深度伪造技术如何被用于虚假信息? 社交媒体平台如何应对AI生成的虚假信息?
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