Deepfakes are impossible to detect
The claim that deepfakes are completely impossible to detect is an overstatement: automated detection tools exist and continue to improve, but the gap between deepfake generation and detection remains significant, and humans alone are poorly equipped to identify modern deepfakes reliably.
What we know
Deepfakes — AI-generated or AI-manipulated video, audio, and images — are a rapidly evolving technology. Contrary to the claim that they are entirely undetectable, multiple detection approaches exist and are deployed by companies, governments, and researchers. However, the detection problem is genuine and serious: as generation technology advances, detection tools often lag behind.
A landmark peer-reviewed study published in iScience (2021) found that humans could correctly identify deepfakes only 57.6% of the time — barely above chance — and that raising awareness or providing financial incentives did not improve accuracy. This establishes that human visual inspection alone is unreliable. A 2025 benchmark study (Deepfake-Eval-2024) found that even the best open-source automated detectors experienced 45–50% drops in accuracy when evaluated on real-world deepfakes collected in 2024, compared to performance on older academic datasets.
However, commercial detection platforms and forensic analysts perform substantially better. The Deepfake-Eval-2024 benchmark found that the best commercial video detectors achieved ~78% accuracy and the best audio systems ~89% accuracy. Human forensic analysts achieve approximately 90% accuracy — higher than current automated systems but still imperfect. DARPA's Media Forensics program and initiatives by Meta, Google, and Microsoft continue to advance detection capabilities.
The practical situation is nuanced: deepfakes that circulate widely on social media are often detectable with dedicated tools, and many AI-generated images and videos carry detectable artifacts. At the same time, the most sophisticated deepfakes created for targeted fraud can defeat both human perception and off-the-shelf detectors. The arms race between generation and detection is ongoing, making neither absolute detectability nor complete undetectability accurate descriptions of the current state.
Common claims
- Humans can reliably spot deepfakes by careful viewing.False — studies show humans identify deepfakes at only slightly above chance rates.
- AI detection tools can reliably identify all deepfakes.False — detection tools perform well on older-style deepfakes but drop sharply on novel real-world examples.
- Deepfakes are impossible to detect.Overstatement — forensic analysts and commercial tools detect many deepfakes, though not all; no method is 100% reliable.
- Deepfakes pose a serious risk to information integrity.Supported — this reflects scientific and government consensus.
Evidence hierarchy
All sources
- Fooled twice: People cannot detect deepfakes but think they caniScience (Cell Press) · 2021
- Deepfake-Eval-2024: A Multi-Modal In-the-Wild BenchmarkarXiv · 2025
- Artificial intelligence, deepfakes, and the uncertain future of truthBrookings Institution · 2022
- Human performance in detecting deepfakes: A systematic reviewComputers in Human Behavior Reports · 2024
- Deepfake Detection TechnologyUK Government Office for Science · 2026