Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings 45th IEEE Symposium on Security and Privacy |
| Seiten | 55-73 |
| Seitenumfang | 19 |
| ISBN (elektronisch) | 979-8-3503-3130-1 |
| Publikationsstatus | Veröffentlicht - 23 Mai 2024 |
Publikationsreihe
| Name | Proceedings - IEEE Symposium on Security and Privacy |
|---|---|
| ISSN (Print) | 1081-6011 |
Abstract
AI-generated media has become a threat to our digital society as we know it. Forgeries can be created automatically and on a large scale based on publicly available technologies. Recognizing this challenge, academics and practitioners have proposed a multitude of automatic detection strategies to detect such artificial media. However, in contrast to these technological advances, the human perception of generated media has not been thoroughly studied yet.In this paper, we aim to close this research gap. We conduct the first comprehensive survey on people's ability to detect generated media, spanning three countries (USA, Germany, and China), with 3,002 participants covering audio, image, and text media. Our results indicate that state-of-the-art forgeries are almost indistinguishable from "real"media, with the majority of participants simply guessing when asked to rate them as human- or machine-generated. In addition, AI-generated media is rated as more likely to be human-generated across all media types and all countries. To further understand which factors influence people's ability to detect AI-generated media, we include personal variables, chosen based on a literature review in the domains of deepfake and fake news research. In a regression analysis, we found that generalized trust, cognitive reflection, and self-reported familiarity with deepfakes significantly influence participants' decisions across all media categories.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Software
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
- Informatik (insg.)
- Computernetzwerke und -kommunikation
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Proceedings 45th IEEE Symposium on Security and Privacy. 2024. S. 55-73 (Proceedings - IEEE Symposium on Security and Privacy).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - A Representative Study on Human Detection of Artificially Generated Media Across Countries
AU - Frank, Joel
AU - Herbert, Franziska
AU - Ricker, Jonas
AU - Schönherr, Lea
AU - Eisenhofer, Thorsten
AU - Fischer, Asja
AU - Dürmuth, Markus
AU - Holz, Thorsten
N1 - Publisher Copyright: © 2024 IEEE.
PY - 2024/5/23
Y1 - 2024/5/23
N2 - AI-generated media has become a threat to our digital society as we know it. Forgeries can be created automatically and on a large scale based on publicly available technologies. Recognizing this challenge, academics and practitioners have proposed a multitude of automatic detection strategies to detect such artificial media. However, in contrast to these technological advances, the human perception of generated media has not been thoroughly studied yet.In this paper, we aim to close this research gap. We conduct the first comprehensive survey on people's ability to detect generated media, spanning three countries (USA, Germany, and China), with 3,002 participants covering audio, image, and text media. Our results indicate that state-of-the-art forgeries are almost indistinguishable from "real"media, with the majority of participants simply guessing when asked to rate them as human- or machine-generated. In addition, AI-generated media is rated as more likely to be human-generated across all media types and all countries. To further understand which factors influence people's ability to detect AI-generated media, we include personal variables, chosen based on a literature review in the domains of deepfake and fake news research. In a regression analysis, we found that generalized trust, cognitive reflection, and self-reported familiarity with deepfakes significantly influence participants' decisions across all media categories.
AB - AI-generated media has become a threat to our digital society as we know it. Forgeries can be created automatically and on a large scale based on publicly available technologies. Recognizing this challenge, academics and practitioners have proposed a multitude of automatic detection strategies to detect such artificial media. However, in contrast to these technological advances, the human perception of generated media has not been thoroughly studied yet.In this paper, we aim to close this research gap. We conduct the first comprehensive survey on people's ability to detect generated media, spanning three countries (USA, Germany, and China), with 3,002 participants covering audio, image, and text media. Our results indicate that state-of-the-art forgeries are almost indistinguishable from "real"media, with the majority of participants simply guessing when asked to rate them as human- or machine-generated. In addition, AI-generated media is rated as more likely to be human-generated across all media types and all countries. To further understand which factors influence people's ability to detect AI-generated media, we include personal variables, chosen based on a literature review in the domains of deepfake and fake news research. In a regression analysis, we found that generalized trust, cognitive reflection, and self-reported familiarity with deepfakes significantly influence participants' decisions across all media categories.
UR - http://www.scopus.com/inward/record.url?scp=85202204511&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2312.05976
DO - 10.48550/arXiv.2312.05976
M3 - Conference contribution
T3 - Proceedings - IEEE Symposium on Security and Privacy
SP - 55
EP - 73
BT - Proceedings 45th IEEE Symposium on Security and Privacy
ER -