GODDS: The Global Online Deepfake Detection System

Abstract

Fake audios, videos, and images are now proliferating widely. We developed GODDS, the Global Online Deepfake Detection system, for a specific user community, namely journalists. GODDS leverages an ensemble of deepfake detectors, along with a human in the loop, to provide a deepfake report on each submitted video/image/audio or VIA artifact submitted to the system. To date, VIA artifacts submitted by over 50 journalists from outlets such as the New York Times, Wall Street Journal, CNN, Agence France Press, and others have been run through GODDS. Unlike other deepfake detection systems, GODDS doesn't just focus on the submitted artifact but automatically derives context about the subject of the VIA artifact. Because context is not always available on all subjects, GODDS focuses on alleged deepfakes of high profile individuals, organizations, and events, where there is likely to be considerable contextual information.

Cite

Text

Postiglione et al. "GODDS: The Global Online Deepfake Detection System." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I28.35367

Markdown

[Postiglione et al. "GODDS: The Global Online Deepfake Detection System." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/postiglione2025aaai-godds/) doi:10.1609/AAAI.V39I28.35367

BibTeX

@inproceedings{postiglione2025aaai-godds,
  title     = {{GODDS: The Global Online Deepfake Detection System}},
  author    = {Postiglione, Marco and Baldwin, Julian and Denisenko, Natalia and Fosdick, Luke and Gao, Chongyang and Gortner, Isabel and Pulice, Chiara and Kraus, Sarit and Subrahmanian, V. S.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {29685-29687},
  doi       = {10.1609/AAAI.V39I28.35367},
  url       = {https://mlanthology.org/aaai/2025/postiglione2025aaai-godds/}
}