Geographic privacy, a crucial aspect of personal security, often goes unnoticed in daily activities. This paper addresses the underestimation of this privacy in the context of increasing online data sharing and the advancements in information gathering technologies. With the surge in the use of Large Multimodal Models, such as GPT-4, for Open Source Intelligence (OSINT), the potential risks associated with geographic privacy breaches have intensified. This study highlights the criticality of these developments, focusing on their implications for individual privacy. The primary objective is to demonstrate the capabilities of advanced AI tools, specifically a GPT-4 based model named "Dr. Watson," in identifying and potentially compromising geographic privacy through online shared content. We developed "Dr. Watson" to analyze and extract geographic information from publicly available data sources. The study involved five experimental cases, each offering different perspectives on the tool's application in extracting precise location data from partial images and social media content. The experiments revealed that "Dr. Watson" could successfully identify specific geographic details, thereby exposing the vulnerabilities in current geo-privacy measures. These findings underscore the ease with which geographic information can be unintentionally disclosed. The paper concludes with a discussion on the broader implications of these findings for individuals and the community at large. It emphasizes the urgency for enhanced awareness and protective measures against geo-privacy leakage in the era of advanced AI and widespread social media usage.

该研究探讨了地理隐私在增加的在线数据共享和信息收集技术进展的背景下被低估的问题，并重点关注了这些发展对个人隐私的影响。研究通过开发名为“Dr. Watson”的基于GPT-4的高级AI工具，从公开数据源中分析和提取地理信息，展示了这些技术的潜在风险，并揭示了当前地理隐私措施的漏洞。结论强调了在高级AI和广泛社交媒体使用时，加强对地理隐私泄露的意识和保护措施的紧迫性。

注意：大型多模态模型正在关注你的地理隐私