论文标题
深度学习生成的社交媒体概况与真实概况没有区别吗?
Are Deep Learning-Generated Social Media Profiles Indistinguishable from Real Profiles?
论文作者
论文摘要
近年来,深度学习方法已经变得越来越有能力产生近乎逼真的图片和类似人类的文本,直到人类无法再识别什么是真实的,什么是AI生成的。关于,有证据表明,其中一些方法已经被采用来生成伪造的社交媒体概况和内容。我们假设这些进步使得对社交媒体的普通用户非常困难,即使不是不可能,这些进步使检测到饲料中产生的虚假社交媒体内容。本文介绍了一个实验的结果,其中375名参与者试图在模拟的社交媒体供稿中标记真实并生成的个人资料和帖子。结果支持我们的假设,并暗示即使是由高级文本生成器写的帖子也很难识别的帖子,即使是完全生成的伪造资料。
In recent years, deep learning methods have become increasingly capable of generating near photorealistic pictures and humanlike text up to the point that humans can no longer recognize what is real and what is AI-generated. Concerningly, there is evidence that some of these methods have already been adopted to produce fake social media profiles and content. We hypothesize that these advances have made detecting generated fake social media content in the feed extremely difficult, if not impossible, for the average user of social media. This paper presents the results of an experiment where 375 participants attempted to label real and generated profiles and posts in a simulated social media feed. The results support our hypothesis and suggest that even fully-generated fake profiles with posts written by an advanced text generator are difficult for humans to identify.