Fears that bias in training sets would mean minorities bearing brunt of scams, fraud and misinformation
Detection tools being developed to combat the growing threat of deepfakes – realistic-looking false content – must use training datasets that are inclusive of darker skin tones to avoid bias, experts have warned.
Most deepfake detectors are based on a learning strategy that depends largely on the dataset that is used for its training. It then uses AI to detect signs that may not be clear to the human eye.
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