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Your privacy is protected by
responsible data practices.
Data plays an important role in making the products and services you use every day more helpful. We are committed to treating that data responsibly and protecting your privacy with strict protocols and innovative privacy technologies.
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Privacy Reviews
Strict privacy protocols are followed throughout every product's development. Privacy is core to how we build our products, with rigorous privacy standards guiding every stage of product development. Each product and feature adheres to these privacy standards, which are implemented through comprehensive privacy reviews. -
AI Ethics & Principles
AI has significant potential to help solve challenging problems, including by advancing medicine, understanding language, and fueling scientific discovery. To realize that potential, it's critical that AI is used and developed responsibly. To that end, we've established principles that guide Google AI applications, best practices to share our work with communities outside of Google, and programs to operationalize our efforts.
Google's COVID-19 Community Mobility Reports use world-class anonymization technology, including differential privacy, to keep user data private, safe, and secure.
Differential Privacy
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Helping organizations anonymize data with
differential privacy
Differential privacy is an advanced anonymization technology that allows us to gain insights from data without compromising the anonymity of our users. We spent over a decade building the largest library of differential privacy algorithms in the world and we open-sourced the library to help organizations easily apply the same privacy protections to their data
Differential privacy is an advanced anonymization technology that allows us to gain insights from data without compromising the anonymity of our users. We spent over a decade building the largest library of differential privacy algorithms in the world and we open-sourced the library to help organizations easily apply the same privacy protections to their data
Resources for Developers
Federated Learning
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Building helpful products and protecting user privacy go hand in hand
Federated learning is a data minimization technology pioneered atGoogle that trains the machine learning models powering many of ourhelpful features, like word predictions, right on your device. This newapproach helps preserve your privacy by delivering helpfulexperiences across our products while keeping your personalinformation on your devices.
Federated learning is a data minimization technology pioneered atGoogle that trains the machine learning models powering many of ourhelpful features, like word predictions, right on your device. This newapproach helps preserve your privacy by delivering helpfulexperiences across our products while keeping your personalinformation on your devices.
Private Join and Compute
How Private Join and Compute works
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Help organizations do more without collecting more data
Private Join and Compute keeps individuals safe while allowing organizations to accurately compute and draw useful insights from aggregate statistics. By sharing the technology more widely, we hope this expands the use cases for secure computing. We'll continue to invest in new research to advance innovations that preserve individual privacy while enabling valuable insights from data.
Private Join and Compute keeps individuals safe while allowing organizations to accurately compute and draw useful insights from aggregate statistics. By sharing the technology more widely, we hope this expands the use cases for secure computing. We'll continue to invest in new research to advance innovations that preserve individual privacy while enabling valuable insights from data.
Resources for Developers
