Concerns that biases in training datasets may lead to minority groups bearing the brunt of fraud, scams, and misinformation. Most deepfake detectors are based on learning strategies that rely on the datasets used for training. Experts are calling for the establishment of more inclusive training datasets and standardized measurement methods to address bias issues in deepfake detection tools.