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A recent study has uncovered a significant privacy risk within a large-scale AI training dataset known as DataComp CommonPool. Researchers discovered that millions of data samples within the set expose highly sensitive personal information, including images of passports, credit cards, and birth certificates. The research, pre-published on arXiv, estimates that hundreds of millions of images contain personally identifiable information (PII). The findings highlight the inherent dangers of indiscriminately scraping data from the internet for AI training purposes, emphasizing that any content posted online is potentially vulnerable to being repurposed in this manner. A key concern raised by the study is the lack of consent, particularly as many of the images predate the widespread adoption of AI, meaning individuals were unaware and unable to authorize the use of their data for this specific application. The study calls on the machine learning community to re-evaluate the ethics of unrestricted web scraping and to address the shortcomings of current privacy regulations in safeguarding personal information within the context of AI training datasets.