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Adobe uses machine learning technologies in Creative Cloud and Document Cloud, such as content analysis and pattern recognition, to offer features and improve our products and services. For example, features such as Content-Aware Fill in Photoshop and facial recognition in Lightroom can be refined using machine learning.
If you access Creative Cloud or Document Cloud via a personal Adobe ID and prefer that Adobe not analyze your files to improve the products and services that we provide to you, you can turn off machine learning at any time from your Adobe Account Management page.
Machine learning is a term that describes how a computer analyzes data and then makes predictions or provides suggestions based on what it learns from that data. It is used to improve and deliver many of the products and services you interact with every day.
A common example of machine learning is an email application that automatically moves messages to your spam folder. The application analyzes the data included in your emails and predicts, from the patterns it discovers, the likelihood that messages are unwanted spam. It then takes action based on that prediction and moves certain messages out of your Inbox and into your spam folder.
When you tag a message as "spam," the application learns from that and continually improves its accuracy of automatically flagging spam mail. The more data that is analyzed by the application, the better the application becomes at a particular task. This process of improving through experience is an example of machine learning.
Adobe uses machine learning for both general product and service improvement as well as to enable specific product features.
A machine learning-enabled feature is a specific functionality or feature that uses machine learning to customize and enhance your experience with certain Adobe products or services. While you cannot opt out of machine learning-enabled features because they are incorporated into Adobe’s software, you can elect not to use a particular machine learning-enabled feature. For example, Content-Aware Fill in Photoshop is a machine learning-enabled feature that uses machine learning to analyze an image and predict the correct content to insert in a selected area. In such features, machine learning is used to enhance your personal experience with a particular product or service and is not used for the general development or improvement of our products and services.
At Adobe, we use machine learning development to improve our products and services, which allows us to deliver innovative and cutting-edge solutions.
We also use machine learning-enabled features to help you be more efficient and creative. For example, we may use machine learning-enabled features to help you organize and edit your images more quickly, accurately, and professionally. With object recognition in Lightroom, we can auto-tag photos of your dog or cat. In Photoshop, machine learning can be used to automatically correct the perspective of an image for you.
We can also use machine learning-enabled features to make content-aware suggestions. For example, if you are working on a UI mock-up, XD might automatically suggest certain buttons. This type of content-aware suggestion can become more relevant to your work when XD learns from your specific usage and data rather than generic data available on the Internet.
We may analyze your usage data and content when it is uploaded, sent, received, or stored using Adobe servers. We may use your content, documents, data, activity logs, and direct feedback to train and improve our algorithms. We may use the aggregate insights we obtain from machine learning to generally improve our products and services.
In the limited circumstances described below, such as when you post content publicly, we may manually review your content to train and improve the algorithms leveraged by our products and services. For example, we may manually identify a dog in an image you post publicly on Behance, and use that data to improve our object recognition algorithm, enabling us to provide more accurate photo search and tagging features. For more information, see “What content do you manually review for machine learning?”
You can find an overview of how Adobe may use information associated with you in the Adobe Privacy Center. We may use the aggregate insights we obtain from machine learning to generally improve our products and services.
Adobe takes your privacy seriously. Your privacy is maintained during machine learning development and none of your data is included in any of our products or features. The insights obtained through machine learning will not be used to re-create your content or any personal information. Our manual review process includes safeguards to help protect your privacy. We only manually review your content in the limited circumstances described below. If you submit non-public content for manual review, we do so only in secure facilities with personnel subject to confidentiality requirements and privacy training. For more information, see “What content do you manually review for machine learning?”
You can find an overview of how Adobe may use your information in the Adobe Privacy Center.
We only manually review your content in the following situations:
If you do not want Adobe to analyze your content using machine learning to improve our products and services, you can opt out at any time by taking the following steps:
The ability to turn off machine learning only applies to customers who access Adobe’s Creative Cloud and Document Cloud products and services via a personal Adobe ID.
This setting also doesn't apply to certain features that allow you to submit content for purposes of improving our products and services using techniques such as machine learning. If you don't want your content to be used for these purposes, you should avoid using those features. These features include:
Additionally, turning off machine learning also doesn't affect your use of features that were developed using machine learning. If you opt out, your content will not be used to improve Adobe products and services using machine learning, but you will still be able to use features that were developed using machine learning.