Original title: Generativní adversariální sítě zdivočely: Veřejné vnímání Deepfake technologií na YouTube
Translated title: GANs gone wild: Public perceptions of Deepfake technologies on YouTube
Authors: Poon, Jessica ; Špelda, Petr (advisor) ; Fitzgerald, James (referee)
Document type: Master’s theses
Year: 2021
Language: eng
Abstract: Deepfake technologies are a form of artificial intelligence (AI) which are based on generative adversarial networks (GANs), a development which has emerged out of deep learning (DL) and machine learning (ML) models. Using a data range which spans the years 2018 - 2021, this research explores public perceptions of deepfake technologies at scale by closely examining commentary found on the social video-sharing platform, YouTube. This open source, ground-level data documents civilian responses to a selection of user-produced, labelled deepfake content. This research fills a gap regarding public perception of this emerging technology at scale. It gauges an underrepresented set of responses in discourse to find that users demonstrate a spectrum of responses which veer between irony and concern, with greater volumes of commentary skewed towards the former. This study of user commentary also finds that YouTube as a wild space ultimately affords reflexive and critical thinking around the subject of deepfake technologies and could prove to be effective as a form of inoculation against disinformation.
Keywords: Artificial Intelligence; Deepfake; Discourse; Politics; Technology

Institution: Charles University Faculties (theses) (web)
Document availability information: Available in the Charles University Digital Repository.
Original record: http://hdl.handle.net/20.500.11956/150489

Permalink: http://www.nusl.cz/ntk/nusl-452621


The record appears in these collections:
Universities and colleges > Public universities > Charles University > Charles University Faculties (theses)
Academic theses (ETDs) > Master’s theses