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“This is a deepfake!”: Celebrity scandals, parodic deepfakes, and a critically speculative ethics of care for fandom research in the age of Artificial Intelligence

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“This is a deepfake!”: Celebrity scandals, parodic deepfakes, and a critically speculative ethics of care for fandom research in the age of Artificial Intelligence . / Li, Eva Cheuk-Yin; Pang, Ka-Wei.
In: Transformative Works and Cultures, Vol. 46, 05.01.2025.

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@article{c311be76ddae4899b84f88249618a0ba,
title = "“This is a deepfake!”: Celebrity scandals, parodic deepfakes, and a critically speculative ethics of care for fandom research in the age of Artificial Intelligence ",
abstract = "Fans are increasingly aware of deepfake—believable AI-fabricated videos—and are therefore more skeptical of unverified information, even when visual evidence appears convincing. This article offers a methodological reflection on analyzing a deepfake event in which fans produced and circulated AI-generated disinformation to playfully undermine the credibility of a celebrity{\textquoteright}s video scandal. We explore the complex human-community-machine interactions (HCMI) between fans and AI-generated images, and we discuss how researchers can ethically (re)present their findings. We call for rethinking the “fan first” principle, a core tenet of ethical fandom research. Drawing on Puig de la Bellacasa{\textquoteright}s technoscientific theorization of care, we propose a critically speculative ethics of care in fandom research, guided by three principles: (1) thinking with fans, (2) thinking for fandom, and (3) thinking beyond fans and fandom. This approach is particularly relevant in a digital media ecology where generative AI and fan practices mutually transform each other. Our discussion also serves as a springboard for further explorations of ethics related to AI, including its impact on trust, social relations, and power in fandom research. ",
keywords = "AI, Counter-information, Disinformation, Ethics of Care, Fans first, Fan studies ethics, Feminist ethics, Human-Community-Machine Interactions (HCMI), Machine learning, Parodic deepfake",
author = "Li, {Eva Cheuk-Yin} and Ka-Wei Pang",
year = "2025",
month = jan,
day = "5",
language = "English",
volume = "46",
journal = "Transformative Works and Cultures",
issn = "1941-2258",
publisher = "Organization for Transformative Works",

}

RIS

TY - JOUR

T1 - “This is a deepfake!”

T2 - Celebrity scandals, parodic deepfakes, and a critically speculative ethics of care for fandom research in the age of Artificial Intelligence

AU - Li, Eva Cheuk-Yin

AU - Pang, Ka-Wei

PY - 2025/1/5

Y1 - 2025/1/5

N2 - Fans are increasingly aware of deepfake—believable AI-fabricated videos—and are therefore more skeptical of unverified information, even when visual evidence appears convincing. This article offers a methodological reflection on analyzing a deepfake event in which fans produced and circulated AI-generated disinformation to playfully undermine the credibility of a celebrity’s video scandal. We explore the complex human-community-machine interactions (HCMI) between fans and AI-generated images, and we discuss how researchers can ethically (re)present their findings. We call for rethinking the “fan first” principle, a core tenet of ethical fandom research. Drawing on Puig de la Bellacasa’s technoscientific theorization of care, we propose a critically speculative ethics of care in fandom research, guided by three principles: (1) thinking with fans, (2) thinking for fandom, and (3) thinking beyond fans and fandom. This approach is particularly relevant in a digital media ecology where generative AI and fan practices mutually transform each other. Our discussion also serves as a springboard for further explorations of ethics related to AI, including its impact on trust, social relations, and power in fandom research.

AB - Fans are increasingly aware of deepfake—believable AI-fabricated videos—and are therefore more skeptical of unverified information, even when visual evidence appears convincing. This article offers a methodological reflection on analyzing a deepfake event in which fans produced and circulated AI-generated disinformation to playfully undermine the credibility of a celebrity’s video scandal. We explore the complex human-community-machine interactions (HCMI) between fans and AI-generated images, and we discuss how researchers can ethically (re)present their findings. We call for rethinking the “fan first” principle, a core tenet of ethical fandom research. Drawing on Puig de la Bellacasa’s technoscientific theorization of care, we propose a critically speculative ethics of care in fandom research, guided by three principles: (1) thinking with fans, (2) thinking for fandom, and (3) thinking beyond fans and fandom. This approach is particularly relevant in a digital media ecology where generative AI and fan practices mutually transform each other. Our discussion also serves as a springboard for further explorations of ethics related to AI, including its impact on trust, social relations, and power in fandom research.

KW - AI

KW - Counter-information

KW - Disinformation

KW - Ethics of Care

KW - Fans first

KW - Fan studies ethics

KW - Feminist ethics

KW - Human-Community-Machine Interactions (HCMI)

KW - Machine learning

KW - Parodic deepfake

M3 - Journal article

VL - 46

JO - Transformative Works and Cultures

JF - Transformative Works and Cultures

SN - 1941-2258

ER -