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

Abstract

Purpose – Recent 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/approach – We 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/implications – The mitigation of DeepFakes call for multi-disciplinary research across the traditional disciplinary boundaries. Practical implications – Government and business sectors need to work together to provide sustainable solutions to the DeepFake problem. Social implications – The 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/value – Unlike 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.

Keywords

• Generative AI
• DeepFakes
• Multimedia forensics