AbstractIntroductionThe present work investigates the natural human ability to recognize and counter the negative impact of deepfake technology. Artificial Intelligence (AI) and machine learning play a crucial role in creating highly realistic synthetic media, known as deepfakes. Deepfakes have become a powerful tool for spreading misinformation and creating inappropriate content. Social media platforms are flooded with such synthetic media, raising serious concerns about the authenticity of digital information directly available to users. Moreover, there is a lack of knowledge and awareness among layman about the authenticity of such media.ObjectiveTo address this issue, manual analysis of hundreds of deepfake images, focusing on identifying visual anomalies without the aid of specialized software or tools, is performed.Materials and MethodsThrough this process, various visual markers are discovered, ranging from common to rare, that can help distinguish deepfake images.ResultsThese indicators are intended to contribute to public awareness and enhance digital media literacy, helping social media users recognize and question the authenticity of deepfake media.ConclusionThis study highlights the importance of identifying visual anomalies and empowering the users to identify and safeguard themselves from deepfakes and its harmful impact.
Malik et al. (Wed,) studied this question.