Murphy Gillian, Flynn Emma
School of Applied Psychology, University College Cork, Cork, Ireland.
Memory. 2021 Apr 28:1-13. doi: 10.1080/09658211.2021.1919715.
Machine-learning has enabled the creation of "deepfake videos"; highly-realistic footage that features a person saying or doing something they never did. In recent years, this technology has become more widespread and various apps now allow an average social-media user to create a deepfake video which can be shared online. There are concerns about how this may distort memory for public events, but to date no evidence to support this. Across two experiments, we presented participants ( = 682) with fake news stories in the format of text, text with a photograph or text with a deepfake video. Though participants rated the deepfake videos as convincing, dangerous, and unethical, and some participants did report false memories after viewing deepfakes, the deepfake video format did not consistently increase false memory rates relative to the text-only or text-with-photograph conditions. Further research is needed, but the current findings suggest that while deepfake videos can distort memory for public events, they may not always be more effective than simple misleading text.
机器学习使得“深度伪造视频”得以制作；这种视频极其逼真，呈现出一个人说着或做着他们从未做过的事情。近年来，这项技术变得更加普及，现在各种应用程序让普通社交媒体用户能够制作可在网上分享的深度伪造视频。人们担心这可能会扭曲对公共事件的记忆，但迄今为止尚无证据支持这一点。在两项实验中，我们向参与者（n = 682）展示了以文本、带照片的文本或带深度伪造视频的文本形式呈现的假新闻故事。尽管参与者认为深度伪造视频令人信服、危险且不道德，并且一些参与者在观看深度伪造视频后确实报告了错误记忆，但与纯文本或带照片文本的情况相比，深度伪造视频格式并没有持续提高错误记忆率。还需要进一步研究，但目前的研究结果表明，虽然深度伪造视频会扭曲对公共事件的记忆，但它们可能并不总是比简单的误导性文本更有效。
