Machine Learning User Study: Call for Volunteers!

Brave is participating in a User Study organized by the University of Cambridge, which aims to enable privacy-preserving Federated Learning to serve advertisements in real-life settings.

For Brave, this means improving our local machine learning models around Brave Ads: better serving offers that interest you during optimal moments in your browsing experience.

We are looking for 500 Brave users 18 years or older to participate using one of our Brave desktop releases on Windows, macOS, or Linux. (Please note: You must live in a region supported by Brave Ads to join the study.)

As a participant, you will have full control and can opt out of the study at any time. In addition, the study will not record any personal data or data about your browsing content, history, etc. However, you will be asked to share some low-sensitivity user behavioral data via your browser, including:

  • Number of open tabs (but not the actual URLs or page content)

  • Time of day you click on an ad (but not what ad)

  • How long you wait before dismissing an ad

Your browser will locally record this low-sensitivity data for 28 days. You can inspect the data your browser records before submitting it for the study, and the data will only remain on your device until you submit it.

At the end of the study, you can enter our prize raffle for a chance to win one of the ten $50 Amazon gift vouchers. There’s also a cool POAP (Proof of Attendance Protocol) NFT (non-fungible token), designed by KaosMixes5, up for grabs!

For more information about the study and how you can participate, please visit:

You can also view the project’s source code on GitHub here.

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