DeepFakes

Uncovering hardcore open source on GitHub

Dados Bibliográficos

ID13086003
AutoresRachel Winter (0000-0002-9596-355X, University of Central Florida, autor correspondente), Andrea Salter (0000-0002-1468-1308, University of Central Florida)
Ano2019
Volume7
Fascículo4
Páginas382-397
Data de publicação2019-10-17
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoPorn Studies (JOURNAL)
Identificadores do periódicoISSN: 2326-8743 • E-ISSN: 2326-8751
EditoraTaylor & Francis (PUBLISHER • GB)
DOI10.1080/23268743.2019.1642794
OpenAlexW2980791294
IdiomaEN
Citações recebidas18
Referências citadas15

In November 2017, a subreddit dedicated to ‘DeepFakes’ brought the work of machine-learning video face-swapping to widespread attention: the new ease of pornographic fakeswapping (focused primarily on celebrities, but also used more broadly to generate a type of revenge porn) became a content regulation topic of discussion on sites such as Pornhub and Reddit. Although the spaces dedicated to sharing these videos were gradually banned or moderated in early 2018, the essential project remains: a series of codebases shared on GitHub, actively situated for open source contributions. In this case study, we will examine the role of GitHub as a platform in the spread of DeepFakes, and interrogate the intersections of the open source ethos and Reddit's approach to moderation, ethics, and anonymity. Ultimately, we find that the DeepFakes project has intentionally spread to spaces with limited moderation, which has allowed the continued creation of non-consensual pornography

Anonymity · Computer security · Data science · Ethos · Face (sociological concept · Internet privacy · Moderation · Open source · Political science · Pornography · Situated · Sociology · World Wide Web · Computer Science · Ethics and Social Impacts of AI · Hate Speech and Cyberbullying Detection · Law · Sexuality, Behavior, and Technology · Artificial Intelligence