Anonymity offers strong guarantees for people to use technology without fear of mass surveillance, identity theft, and data mis-use. To anonymize and share data widely, de-identification is the main tool used in academia and industry. Yet mounting evidence suggest that de-identification may not protect people’s privacy in practice. We present The Observatory of Anonymity, an interactive website demonstrating how few pieces of personal data can easily re-identify us. Taking advantage of modern web technologies, it al-lows participants to explore their correctness score—the likelihood to be correctly and uniquely identified from their demographics only. Trained on census data from 89 countries, it demonstrates the effectiveness of re-identification attacks on deemed-anonymous data. The website further allows analysts to upload their own data samples to train our machine learning models in real time. The Observatory provides a unique tool for individuals, researchers, and practitioners to assess whether current de-identification practices satisfy the anonymization standards of modern data protection laws such as GDPR and CCPA.