Designing Effective Digital Literacy Interventions for Boosting Deepfake Discernment

TL;DR

This study evaluates five digital literacy interventions to improve people's ability to detect deepfake images, demonstrating that simple, accessible methods can significantly enhance discernment without reducing trust in real images.

Contribution

It compares the effectiveness of five novel digital literacy strategies for deepfake detection through a large-scale experiment with immediate and long-term assessments.

Findings

Interventions increased deepfake detection accuracy by up to 13 percentage points.

Lightweight and easy-to-understand methods are effective for improving discernment.

Trust in real images was maintained after interventions.

Abstract

Deepfakes images can erode trust in institutions and compromise election outcomes, as people often struggle to discern real images from deepfake images. Improving digital literacy can help address these challenges. Here, we compare the efficacy of five digital literacy interventions to boost people's ability to discern deepfakes: (1) textual guidance on common indicators of deepfakes; (2) visual demonstrations of these indicators; (3) a gamified exercise for identifying deepfakes; (4) implicit learning through repeated exposure and feedback; and (5) explanations of how deepfakes are generated with the help of AI. We conducted an experiment with N=1,200 participants from the United States to test the immediate and long-term effectiveness of our interventions. Our results show that our lightweight, easy-to-understand interventions can boost deepfake image discernment by up to 13 percentage points while maintaining trust in real images.