With coding having emerged as one of the best use cases for LLMs, Google is reportedly looking to train its AI models with code from actual Android app developers, but is at least paying them to do so.

404 Media reports that a “confidential” program sees Google (trying to) quietly purchase Android app code from Play Store developers specifically to train its AI models. In an email to app developers, Google positions the “confidential content offer pilot” as a way to “generate additional revenue from your apps.”

Google says that the code purchased is being used “to help improve Google’s developer tools and products,” with a link in the email going to a page about “partnerships to improve our AI products.” The email itself apparently does not mention AI at all.

The email reads:

We are reaching out on behalf of the Google Partnerships team with an invitation for a select group of Google Play app developers to join a confidential content offer pilot.

We’d like to offer a unique opportunity to generate additional revenue from your apps. You’ve put a lot of hard work into building your app and growing its user base. Whether it’s the active production codebase powering your current app, or archives of prototypes and side projects no longer in use, that code could have untapped value. This is a unique occasion to help transform tools and products, support the developer ecosystem, and unlock new revenue.

The Opportunity: We are looking for high-quality, real-world codebases to help improve Google’s developer tools and products. Here is what this program offers you:

• Additional revenue opportunities: Get paid for sharing the code powering your apps, as well as your archived projects.
• Be an early adopter: As a pilot partner, you will shape how Google partners with the developer community moving forward.

Human-made content is frequently used to train AI models, including public-facing content from online publishers. That content is rarely ever paid for by companies such as Google, but Android app code is technically private – at the very least generally not published fully online.

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