Gemini for Google Cloud lets you use AI-powered assistance while
conforming to
[Google's privacy commitment](https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-unveils-ai-and-ml-privacy-commitment)
with generative AI technologies. When you use Gemini in the
Google Cloud console or in a development environment, Google Cloud
[handles your prompts](https://docs.cloud.google.com/gemini/docs/discover/data-governance.md.txt#submit-receive-data) in accordance with the
[terms of service](https://cloud.google.com/terms) and
[Cloud Data Processing Addendum](https://cloud.google.com/terms/data-processing-addendum).

For more information about Gemini products in Google Cloud, see
[Google Cloud with Gemini overview](https://docs.cloud.google.com/gemini/docs/overview.md.txt).

## Google's privacy commitment

Google was one of the first in the industry to publish an [AI/ML privacy
commitment](https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-unveils-ai-and-ml-privacy-commitment),
which outlines our belief that customers should have the highest level of
security and control over their data that's stored in the cloud. That commitment
extends to Google Cloud generative AI products. Google helps ensure that
its teams are following these commitments through robust data governance
practices, which include reviews of the data that Google Cloud uses in the
development of its products. You can find more details about how Google
processes data in
[Customer Data Processing Addendum (CDPA)](https://cloud.google.com/terms/data-processing-addendum)
or the data
processing agreement applicable to your Google Cloud service.

## Data you submit and receive

The questions that you ask Gemini, including any input
information or code that you submit to Gemini to analyze or
complete, are called *prompts* . The answers or code completions that you receive
from Gemini are called *responses*.

Gemini doesn't use your prompts or its responses as data to
train its models. Some features are only available through the
[Gemini for Google Cloud Trusted Tester Program](https://cloud.google.com/gemini-for-cloud/ttp/welcome),
which lets you optionally share data, but the data is used for product
improvements, not for training Gemini models.

[Code customization](https://docs.cloud.google.com/gemini/docs/codeassist/code-customization-overview.md.txt) lets
you get code suggestions based on your organization's private codebase directly
from Gemini Code Assist. When you use code customization, we
securely access and store your private code. This access and storage is
essential for delivering the code customization service you've requested. To
configure and use code customization, see
[Configure and use Gemini Code Assist code customization](https://docs.cloud.google.com/gemini/docs/codeassist/code-customization.md.txt).

Because Gemini is an evolving technology, it can generate output
that's plausible-sounding but factually incorrect. We recommend that you
validate all output from Gemini before you use it. For more
information, see
[Gemini products in Google Cloud and responsible AI](https://docs.cloud.google.com/gemini/docs/discover/responsible-ai.md.txt).

## Encryption of prompts

When you submit prompts to Gemini, your data is encrypted
in-transit as input to the underlying model in Gemini. For more
information on Gemini data encryption, see
[Default encryption at rest](https://docs.cloud.google.com/docs/security/encryption/default-encryption.md.txt) and
[Encryption in transit](https://docs.cloud.google.com/docs/security/encryption-in-transit.md.txt).

## Program data generated from Gemini

Gemini is trained on first-party Google Cloud
code as well as selected third-party code. You're responsible for the
security, testing, and effectiveness of your code, including any code
completion, generation, or analysis that Gemini offers you.

Gemini also provides source citations when suggestions directly
quote at length from a source to help you comply with any license requirements.

Because responses in Gemini are generated from a model that's
trained on many lines of code, you should exercise the same care with
Gemini-provided code that you would with any other code. Make
sure that you test the code properly and check for security vulnerabilities,
incompatibilities, and other potential issues.

## What's next

- Learn about the [security, privacy, and compliance of Gemini Code Assist](https://docs.cloud.google.com/gemini/docs/codeassist/security-privacy-compliance.md.txt).