My NSFW video has partial occlusion: deepfakes and the technological production of non-consensual pornography

Newton, Olivia B.; Stanfill, Mel

doi:10.1080/23268743.2019.1675091

Cited by 16 publications

(24 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Furthermore, the reviewed articles contain several references to the use of deepfakes to create sexually explicit or pornographic content (e.g. Newton and Stanfill, 2020; Popova, 2019). The creation of such content involves the digital replacement of the face of one person with that of another who is involved in a sexual act.…”

Section: Discussionmentioning

confidence: 99%

“…These anti-deepfake arguments also emphasize the gendered nature of the narrative emerging from the process and the violence connected to it (Eelmaa, 2022; Flynn et al. , 2021; Gregory, 2022; Newton and Stanfill, 2020; Widder et al. , 2022; Winter and Salter, 2020) including cybercrime (Ali et al.…”

Section: Conceptual Framework Of Deepfake Engagementmentioning

confidence: 99%

“…, 2021; Bode, 2021; Eelmaa, 2022; Gamage et al. , 2022; Newton and Stanfill, 2020; de Seta, 2021; Widder et al. , 2022).…”

Section: Conceptual Framework Of Deepfake Engagementunclassified

“…, 2021; Bode, 2021; de Seta, 2021; Widder et al. , 2022), a means to engage with the celebrity being deepfaked (Bode, 2021; Popova, 2019) and an opportunity to showcase technological expertise and hone skills (Newton and Stanfill, 2020). Pro-deepfake opinions also indicate that widespread use of deepfake technology is inevitable (Widder et al.…”

Section: Conceptual Framework Of Deepfake Engagementmentioning

confidence: 99%

“…First, platforms provide technical enthusiasts an incredible opportunity to train and master deepfake creation abilities (Gamage et al. , 2022; Newton and Stanfill, 2020; Widder et al. , 2022).…”

Section: Conceptual Framework Of Deepfake Engagementmentioning

confidence: 99%

See 4 more Smart Citations

Engaging with deepfakes: a meta-synthesis from the perspective of social shaping of technology theory

Vasist

Krishnan²

2022

INTR

View full text Add to dashboard Cite

PurposeThis study aims to establish a comprehensive understanding of the intricacies of how individuals engage with deepfakes, focusing on limiting adverse effects and capitalizing on their benefits.Design/methodology/approachThis study conducted a meta-synthesis of qualitative studies on deepfakes, incorporating study-specific analysis followed by a cross-study synthesis.FindingsBased on the meta-synthesis, the study developed an integrated conceptual framework based on the perspectives from the social shaping of technology theory embedding deepfake-related assertions, motivations, the subtleties of digital platforms, and deepfake-related repercussions.Research limitations/implicationsThe study offers crucial insights into the evolving nature of deepfakes as a socio-technical phenomenon and the significance of platform dynamics in deepfake production. It enables researchers to comprehend the cascading effects of deepfakes and positions them to evaluate deepfake-related risks and associated mitigation mechanisms.Practical implicationsThe framework that emerges from the study illustrates the influence of platforms on the evolution of deepfakes and assists platform stakeholders in introducing effective platform governance structures to combat the relentless proliferation of deepfakes and their consequences, as well as providing guidance for governments and policymakers to collaborate with platform leaders to set guardrails for deepfake engagement.Originality/valueDeepfakes have been extensively contested for both their beneficial and negative applications and have been accused of heralding an imminent epistemic threat that has been downplayed by some quarters. This diversity of viewpoints necessitates a comprehensive understanding of the phenomenon. In responding to this call, this is one of the first to establish a comprehensive, theoretically informed perspective on how individuals produce, process, and engage with deepfakes through a meta-synthesis of qualitative literature on deepfakes.

show abstract

Section: Discussionmentioning

confidence: 99%