深度造假为何如此之深?深度造假技术学术叙事的多学科主题分析

John Twomey;Didier Ching;Matthew Peter Aylett;Michael Quayle;Conor Linehan;Gillian Murphy
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引用次数: 0

摘要

Deepfakes是一种合成媒体,它使用深度学习技术来制作虚假的图像、视频和音频。这项技术的出现引发了众多学科学者的评论和猜测,他们就深度假货扩散对法律、政治和娱乐等领域的影响发表了专家意见。进行了系统的范围审查,以识别、收集和批判性地分析这些学术叙述。其目的是建立和批评之前对该技术的定义和对深度伪造技术的危害和好处进行分类的尝试。在一系列数据库中检索2017年至2023年的相关文章,得到102篇论文的大型多学科数据集,长度为181659个单词,通过主题分析对其进行定性分析。对未来研究的影响包括质疑缺乏研究证据来证明深度伪造的所谓积极作用,认识到身份在深度伪造技术中所起的作用,挑战深度伪造的可访问性/可信度,并提出一种更细致入微的方法来解决深度伪造的“积极和消极”二分法。此外,我们还展示了关于什么是深度伪造与其他形式的虚假媒体的定义问题如何使人们对深度伪造的新颖性和影响感到困惑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What Is So Deep About Deepfakes? A Multi-Disciplinary Thematic Analysis of Academic Narratives About Deepfake Technology
Deepfakes are a form of synthetic media that uses deep-learning technology to create fake images, video, and audio. The emergence of this technology has inspired much commentary and speculation from academics across a range of disciplines, who have contributed expert opinions regarding the implications of deepfake proliferation on fields such as law, politics, and entertainment. A systematic scoping review was carried out to identify, assemble, and critically analyze those academic narratives. The aim is to build on and critique previous attempts at defining the technology and categorizing the harms and benefits of deepfake technology. A range of databases were searched for relevant articles from 2017 to 2023, resulting in a large multi-disciplinary dataset of 102 papers, 181,659 words long, which were analyzed qualitatively through thematic analysis. Implications for future research include questioning the lack of research evidence for the supposed positives of deepfakes, recognizing the role that identity plays in deepfake technology, challenging the perceived accessibility/ believability of deepfakes, and proposing a more nuanced approach to the dichotomous “positive and negatives” of deepfakes. Furthermore, we show how definitional issues around what a deepfake is versus other forms of fake media feeds confusion around the novelty and impacts of deepfakes.
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