Deepfake detection improves when using algorithms that are more aware of demographic diversity

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The story "Deepfake detection improves when using algorithms that are more aware of demographic diversity" was covered 1 days ago by The Next Web, a news publisher based in Netherlands.

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The Next Web 1d ago

Deepfake detection improves when using algorithms that are more aware of demographic diversity - The Next Web

Quick Summary:

Recent examples of deepfakes include Taylor Swift nude images, an audio recording of President Joe Biden telling New Hampshire residents not to vote, and a video of Ukrainian President Volodymyr Zelenskyy calling on his troops to lay down their arms.

Deepfakes – essentially putting words in someone else’s mouth in a very believable way – are becoming more sophisticated by the day and increasingly hard to spot.

Although companies have created detectors to help spot deepfakes, studies have found that biases in the data used to train these tools can lead to certain demographic groups being unfairly targeted.