Deepfakes are becoming increasingly sophisticated, making it harder to distinguish real from fake. But can the powerful language model, ChatGPT, help us identify these deceptive videos and audio recordings? New research explores ChatGPT's potential as a deepfake detector, comparing its performance to specialized AI models and even human perception. The study reveals that while ChatGPT wasn't explicitly designed for this task, it shows some promise. By analyzing videos and audio for inconsistencies, it can often flag potential deepfakes. The effectiveness, however, hinges on how it's prompted. Simple yes/no questions aren't enough; ChatGPT needs detailed instructions that guide its analysis towards specific visual and auditory artifacts. While ChatGPT's performance is comparable to that of humans, it still lags behind dedicated deepfake detection AI models, which achieve significantly higher accuracy rates due to specialized training. The research also uncovers ChatGPT's limitations, particularly its reliance on traditional analysis techniques rather than cutting-edge deep learning methods. This highlights a core challenge: while LLMs offer interpretability, they currently lack the power of specialized forensic tools. Future research aims to combine the strengths of both approaches, merging the analytical prowess of LLMs with the accuracy of deep learning models, creating more robust and explainable deepfake detection systems. This could lead to more transparent and trustworthy tools for identifying manipulated media in an age where distinguishing reality from fabrication is increasingly crucial.