Digital literacy interventions can boost humans in discerning deepfakes

Authors: Dominique Geissler, Claire Robertson, Stefan Feuerriegel

Published: 2025-07-31 12:23:45+00:00

AI Summary

The research investigates the effectiveness of five digital literacy interventions in improving people's ability to discern deepfakes. The study found that textual and visual interventions significantly boosted deepfake discernment without reducing trust in real images, although the effect was not entirely sustained long-term.

Abstract

Deepfakes, i.e., images generated by artificial intelligence (AI), can erode trust in institutions and compromise election outcomes, as people often struggle to discern real images from deepfakes. Improving digital literacy can help address these challenges, yet scalable and effective approaches remain largely unexplored. 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 interventions can boost deepfake discernment by up to 13 percentage points while maintaining trust in real images. Altogether, our approach is scalable, suitable for diverse populations, and highly effective for boosting deepfake detection while maintaining trust in truthful information.


Key findings
Textual and visual interventions significantly improved immediate deepfake discernment, while the impact on long-term discernment was less pronounced. No intervention significantly decreased trust in real images or increased skepticism.
Approach
The study used a between-subjects experiment with 1200 US participants randomly assigned to one of five digital literacy interventions (textual, visual, gamified, feedback, knowledge) or a control group. Participants completed image discernment tasks before and after a two-week period to assess immediate and long-term effects.
Datasets
A dataset of 10 real images and 20 deepfakes, split into two sets (A and B) for a counter-balanced design, sourced from various sources including Flickr, Midjourney, DALL-E 3, and news outlets.
Model(s)
UNKNOWN
Author countries
Germany,USA,Canada