The increasing complexity of privacy policies in mobile applications (called apps) necessitates a user-friendly approach to convey data practices. This research, therefore, delves into the realm of data safety documentation within the Android ecosystem, particularly focusing on Google’s Data Safety Documents. Recognizing the complexity and often overwhelming nature of traditional privacy policies, this paper seeks to understand how well these more concise, user-oriented documents serve the average user. Through a comprehensive survey, we assess the general user’s grasp of the information provided in these documents. Furthermore, we utilize advanced language models like ChatGPT to analyze and interpret the contents, aiming to offer a clearer, more accessible version of the data practices described. Our findings reveal a notable disconnect between the technical language used in these documents and the average user’s comprehension. This gap highlights the urgency for more straightforward and standardized communication methods in the presentation of data practices. Our study contributes to the broader discourse on data privacy by proposing a methodology to enhance the transparency and user-friendliness of data safety information, thereby empowering users to make more informed decisions regarding their data privacy in the mobile app sphere.