Deepfake Labels Restore Reality, Especially for Those Who Dislike the Speaker

TL;DR

This study shows that labeling videos as real or deepfake improves people's ability to distinguish between true and fake information, with political attitudes influencing detection accuracy.

Contribution

The paper demonstrates that labeling deepfake videos enhances misinformation detection and explores how political bias affects this ability.

Findings

Participants recalled 93.8% of deepfake videos

Labeling aids in misinformation combat

Political bias influences detection accuracy

Abstract

Deepfake videos create dangerous possibilities for public misinformation. In this experiment (N=204), we investigated whether labeling videos as containing actual or deepfake statements from US President Biden helps participants later differentiate between true and fake information. People accurately recalled 93.8% of deepfake videos and 84.2% of actual videos, suggesting that labeling videos can help combat misinformation. Individuals who identify as Republican and had lower favorability ratings of Biden performed better in distinguishing between actual and deepfake videos, a result explained by the elaboration likelihood model (ELM), which predicts that people who distrust a message source will more critically evaluate the message.