Deepfakes and the 2020 US elections: what (did not) happen

Authors: João Paulo Meneses

Published: 2021-01-22 13:10:47+00:00

AI Summary

This paper analyzes why malicious deepfakes did not significantly impact the 2020 US elections, despite widespread predictions. It attributes this to a confluence of factors including increased social media platform activity, new legislation, the difficulty of accessing AI for malicious purposes, and heightened societal awareness of disinformation.

Abstract

Alarmed by the volume of disinformation that was assumed to have taken place during the 2016 US elections, scholars, politics and journalists predicted the worst when the first deepfakes began to emerge in 2018. After all, US Elections 2020 were believed to be the most secure in American history. This paper seeks explanations for an apparent contradiction: we believe that it was precisely the multiplication and conjugation of different types of warnings and fears that created the conditions that prevented malicious political deepfakes from affecting the 2020 US elections. From these warnings, we identified four factors (more active role of social networks, new laws, difficulties in accessing Artificial Intelligence and better awareness of society). But while this formula has proven to be effective in the case of the United States, 2020, it is not correct to assume that it can be repeated in other political contexts.


Key findings
The 2020 US election was remarkably free from significant influence by malicious deepfakes. This was likely due to a combination of factors, including increased efforts by social media platforms to remove harmful content and new legislation aimed at combating deepfakes. The paper cautions that this success may not be replicable in other contexts.
Approach
The paper uses a qualitative approach, analyzing existing literature and reports to identify four key factors that contributed to the lack of malicious deepfake influence on the 2020 US elections: proactive social media moderation, new legislation, difficulties in accessing AI technology, and increased public awareness of disinformation.
Datasets
UNKNOWN
Model(s)
UNKNOWN
Author countries
Portugal