A developer scraped nearly 2 million photos from Airbnb listings and used machine learning to identify properties potentially used as opium dens. The project, which involved parallel processing of images, aimed to uncover illicit activities hiding in plain sight on the popular rental platform. The developer shared the work on Hacker News, noting the technical challenges and the possible legal ramifications of scraping such data.
The analysis focused on detecting visual cues associated with opium smoking, such as specific pipes, lamps, or setups. While the developer did not name names or publish specific findings, the project highlights how AI can be used to monitor vast amounts of public data for illegal or dangerous activities.
However, the endeavor also raises serious privacy and legal questions. Scraping Airbnb photos may violate the platform's terms of service, and using AI to target particular cultures or neighborhoods could lead to bias or discrimination. The developer acknowledged these concerns, stating that the project was more of a technical proof-of-concept than a deployable tool.
"This is a grey area," the developer wrote. "The data is publicly visible, but scraping it at scale and applying AI for this purpose could get you sued."
The work has sparked debate on Hacker News about the balance between public safety and platform privacy, with many commenters questioning the ethics and legality of such mass surveillance techniques.