DeepFake the menace: mitigating the negative impacts of AI-generated content

Author:

Lyu Siwei

Abstract

PurposeRecent years have witnessed an unexpected and astonishing rise of AI-generated (AIGC), thanks to the rapid advancement of technology and the omnipresence of social media. AIGCs created to mislead are more commonly known as DeepFakes, which erode our trust in online information and have already caused real damage. Thus, countermeasures must be developed to limit the negative impacts of AIGC. This position paper aims to provide a conceptual analysis of the impact of DeepFakes considering the production cost and overview counter technologies to fight DeepFakes. We will also discuss future perspectives of AIGC and their counter technology.Design/methodology/approachWe summarize recent developments in generative AI and AIGC, as well as technical developments to mitigate the harmful impacts of DeepFakes. We also provide an analysis of the cost-effect tradeoff of DeepFakes.Research limitations/implicationsThe mitigation of DeepFakes call for multi-disciplinary research across the traditional disciplinary boundaries.Practical implicationsGovernment and business sectors need to work together to provide sustainable solutions to the DeepFake problem.Social implicationsThe research and development in counter-technologies and other mitigation measures of DeepFakes are important components for the health of future information ecosystem and democracy.Originality/valueUnlike existing reviews in this topic, our position paper focuses on the insights and perspective of this vexing sociotechnical problem of our time, providing a more global picture of the solutions landscape.

Publisher

Emerald

Reference54 articles.

1. Mesonet: a compact facial video forgery detection network,2018

2. Detecting ai-synthesized speech using bispectral analysis,2019

3. Wasserstein GAN;arXiv preprint arXiv:170107875,2017

4. Avatarify (2022), available at: https://avatarify.ai/

5. A robust GAN-generated face detection method based on dual-color spaces and an improved Xception,2021

Cited by 1 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. Advancements in Deepfake Detection : A Review of Emerging Techniques and Technologies;International Journal of Scientific Research in Computer Science, Engineering and Information Technology;2024-09-05

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