AllTrails, the leading publisher of trail guides and maps for hiking, camping, mountain biking, climbing, and snowsports announced today that it had developed a new AI (artificial intelligence) called TrailGPT for proofreading and correcting the crowdsourced trail reports and recommendations submitted by its millions of users.
“While AllTrails is the go-to mobile app for many outdoor adventurers, it’s not always that accurate when it comes to trail names, distances, or difficulty levels,” said HAL Langley, the AllTrails director of data quality. “While we encourage our users to carry a paper map, check the weather, and research local conditions before they venture outdoors, few do, much to the dismay of Search and Rescue Authorities across the United States.”
Therefore, with help from Microsoft and OpenAI Corporation, AllTrails created an artificial intelligence program called TrailGPT that processes all of the trip reports, comments, and images shared by its users and correlates them with USGS maps, social media posts and photos, and other authoritative sources. The goal was to clean up its user-submitted data and generate guidebook quality trail information that dovetails with actual trail names and standardized difficulty ratings.
“The difficult part for TrailGPT in processing all this data was in deciding which information is trustworthy and which information is spurious. It’s a lot like reading online product reviews if you think about it. Some are from people who know what they’re talking about but most reviews are written by less “experienced and detail-oriented” people, to be generous. It’s the same thing with our crowdsourced user trail reports,” said HAL.
Another problem faced by TrailGPT and its trainers is the temporal nature of AllTrail’s user data. Trail reports and trail photos are perishable over time because the routes that trails follow change over time, either from overuse or because they’re disrupted by the weather. But understanding time is a real challenge for AI programs because, not being human, they operate in a world that is timeless and static. TrailGPT’s trainers couldn’t explain time to the AI, but they were able to tweak its learning algorithm to give less credence to older trip reports, images, and geographic data than newer sources, much the same way that humans do.
The AllTrails team also had to address the lingering question about whether it is legal to use data you don’t own to train an AI. For example, TrailGPT was trained using AllTrail’s crowdsourced data in addition to authoritative guidebooks, social media posts and images, and other third-party sources that it did not own or have explicit permission to use. “We felt comfortable using third-party copyrighted sources to train TrailGPT because we were creating a derivative work, not a copy of those sources, just like a human author doing research for a book would do”, said Dexter Reilly, AllTrail’s General Counsel. “Because our use is transformative, it falls under the copyright Fair Use Doctrine.”
When will the results of TrailGPT’s trail curation work go public? “We’re very excited to unveil a more accurate and up-to-date catalog of trail data and see what our user base thinks about it,” says HAL Langley. “Beginning this Spring (2023), we’ll provide free access to a beta of the curated TrailGPT version of AllTrails for all of our licensed app users. After three months, we’ll begin to charge for it as a premium offering that costs more than our regular app. It’s just like a guidebook: if you want the best and most accurate maps and trial beta, you have to pay for it. If not, you can continue to use the crowdsourced data we currently publish.”
Yes, I know that today is March 31st and not April 1, but we wanted to publish this post on a weekday and not wait until the weekend (when we’ll be hiking).
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