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Computer Science > Human-Computer Interaction

Title: As Good As A Coin Toss: Human detection of AI-generated images, videos, audio, and audiovisual stimuli

Abstract: As synthetic media becomes progressively more realistic and barriers to using it continue to lower, the technology has been increasingly utilized for malicious purposes, from financial fraud to nonconsensual pornography. Today, the principal defense against being misled by synthetic media relies on the ability of the human observer to visually and auditorily discern between real and fake. However, it remains unclear just how vulnerable people actually are to deceptive synthetic media in the course of their day to day lives. We conducted a perceptual study with 1276 participants to assess how accurate people were at distinguishing synthetic images, audio only, video only, and audiovisual stimuli from authentic. To reflect the circumstances under which people would likely encounter synthetic media in the wild, testing conditions and stimuli emulated a typical online platform, while all synthetic media used in the survey was sourced from publicly accessible generative AI technology.
We find that overall, participants struggled to meaningfully discern between synthetic and authentic content. We also find that detection performance worsens when the stimuli contains synthetic content as compared to authentic content, images featuring human faces as compared to non face objects, a single modality as compared to multimodal stimuli, mixed authenticity as compared to being fully synthetic for audiovisual stimuli, and features foreign languages as compared to languages the observer is fluent in. Finally, we also find that prior knowledge of synthetic media does not meaningfully impact their detection performance. Collectively, these results indicate that people are highly susceptible to being tricked by synthetic media in their daily lives and that human perceptual detection capabilities can no longer be relied upon as an effective counterdefense.
Comments: For study pre-registration, see this https URL
Subjects: Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Sound (cs.SD); Audio and Speech Processing (eess.AS)
MSC classes: 68T01
ACM classes: I.2
Cite as: arXiv:2403.16760 [cs.HC]
  (or arXiv:2403.16760v3 [cs.HC] for this version)

Submission history

From: Di Cooke [view email]
[v1] Mon, 25 Mar 2024 13:39:33 GMT (359kb)
[v2] Tue, 26 Mar 2024 15:17:51 GMT (359kb)
[v3] Thu, 4 Apr 2024 14:51:56 GMT (363kb)

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