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Think GeoGuessr is fun? Try using ChatGPT to guess locations in your photos
People have found a new use for ChatGPT: Figuring out locations from photos.
OpenAI’s latest AI models, o3 and o4-mini, can analyze images beyond just recognizing objects; they can zoom in, crop, and detect visual clues in photos to help identify places, landmarks, and even specific businesses. This capability is fascinating, but it’s also raised some privacy concerns about how easily people can use AI to reverse-engineer location data from images.
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TechCrunch reported that people are uploading photos — anything from restaurant menu snapshots to casual selfies — and asking ChatGPT to guess where they were taken. The AI does this by looking at everything in the image: the type of buildings, landscape features, and even subtle hints like the architecture or the layout of a city. It then taps into its knowledge database and sometimes the internet to make an educated guess about the location. The results can be surprisingly accurate, and it’s got people talking.
Some users have even tested the AI with blurry photos or images with partial objects, and the model still managed to make a guess.
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I love playing GeoGuessr, a game where you’re dropped into a random location on Google Street View and have to guess where you are based on the surroundings. So this ChatGPT capability was super fun to test myself. I uploaded a few photos to see how ChatGPT would handle the challenge. However, as with any AI, the result was not always perfect.
Interpreting visual clues
The first photo was a picture of my house. ChatGPT immediately guessed the location, though not based on metadata. Instead, it made an educated guess by analyzing the glacier boulder in the side yard, the types of trees visible in the photo, and the wood siding on the houses around me. It mentioned that this combination of natural features and architectural styles was typical of the region I had previously mentioned in a conversation — where I’m from. It was accurate but still relied on some prior context, which made me wonder how much of this was due to our earlier conversation.
For the second photo, I uploaded an image of a building with part of an office sign visible. ChatGPT quickly zoomed in on the sign and used the partial information to narrow down the location. It didn’t take long before it deduced the city and even the area where the building was located. I was impressed with how the model used such a small visual clue to make a fairly precise guess.
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For my third test, I gave it a more challenging photo: a scenic view with no obvious landmarks. ChatGPT explained that while it could analyze the image for visual clues, it needed distinctive landmarks or location tags to make a confident guess. It also mentioned that without GPS data or EXIF tags, it could only read the scene itself — trees, buildings, terrain — and would be less certain in its guess.
I played with ChatGPT a few more times after this and noticed the AI starting to get more stubborn about not identifying locations in my photos. It’d tell me that it would try to narrow down the options, but it needed more data to go on to give me an accurate answer.
Still, one of the main reasons people seem drawn to this trend is because ChatGPT does analyze more than just the obvious features of a photo. Even without metadata like EXIF data or other direct data extraction, the AI interprets visual clues.
Privacy concerns
This experiment made me realize how powerful, and sometimes eerie, these AI models can be when it comes to “reverse location searches” from photos — even if they aren’t great at it yet. It also made me think about the privacy concerns.
Also: OpenAI’s most impressive move has nothing to do with AI
While AI tools can be fun and useful at times, it’s important to be aware of the risks involved in sharing your images online and how people can use AI to analyze the data in those images, whether embedded or just visual, to figure out where it was taken.
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