Artificial Intelligence (AI) is a type of computer science. It develops systems that can assist with tasks that may require human-like intelligence, such as problem-solving and understanding language. There are two forms of classical AI:
At Pinterest, we’ve always used both forms of classical AI to help people find inspiration to create a life they love. This can show up in a variety of ways, including:
Where appropriate, we use human reviewers and feedback from the public to refine our AI. We continuously monitor and evaluate our methods to work to ensure the experiences are working as intended.
Machine learning involves the development of algorithms and statistical models. It helps computers learn from and make decisions based on existing data. Machine learning systems are built to perform specific tasks, but are not manually programmed to do so. Instead, these systems find patterns, make predictions and can improve performance over time as more data is gathered.
Traditional machine learning is primarily about predicting or classifying existing data. For example, to teach a computer to recognize chairs in photos using machine learning, you'd show it a lot of pictures of chairs, and items that aren’t chairs. Then, the computer will learn by itself to tell the difference.
At Pinterest, we use machine learning in many different areas of the business. For example, we use it to recommend and show the most relevant ideas across home feed, search and related feeds. We also use it to increase inclusive representation across Pinterest’s recommendation feeds, such as diverse body types.
We’re thoughtfully exploring Generative AI (or Gen AI) technology that drives innovation and creativity. For example, we use Gen AI technology to make ads more engaging and improve campaign performance for advertisers by
We have taken steps to help ensure the responsible use of Gen AI. Our
We’re always making efforts to enhance our content moderation systems. As part of this, we have partnered with the Digital Trust and Safety Partnership (DTSP) and participated in their Gen AI and Automations Working Group.
Our
The labeling of AI-generated or modified content helps to provide relevant context about the content people see on Pinterest.
Pinterest will show a label on the close-up of an image Pin if the content owner identifies that the content was modified or generated with AI.
In addition, Pinterest will show a label on the close-up of an image Pin when Pinterest’s detection systems identify that it may have been generated or altered with AI. This is according to the
Learn more about Gen AI labels and our appeals process in
Pinterest’s Navigator is a family of multimodal foundation models that ingests text and image inputs to power text-based outputs for a variety of Pinterest features, including conversational experiences. Navigator was built by fine-tuning a publicly available open-source base language model, using a combination of synthetic data, public content on the platform, and usage data for AI-powered features. Pinterest used more than 150,000 data points composed of synthetically generated training text examples that simulate realistic multiturn conversations, more than 1,000,000 multimodal data points composed of image and text samples and more than 100,000 data points composed of conversational logs in its training. Training the Navigator family of models using synthetic data began in January 2026. The time period for collection on content dates to the launch of Pinterest in 2010 and usage data for AI features began being collected after October 2026. The data collection is ongoing. The datasets were rated, cleaned, and processed for quality purposes and to meet our trust, safety, and other internal standards.
The synthetic data was not licensed or purchased from third parties and does not include personal information or aggregate consumer information. Public content on the platform may be protected under copyright, trademark, or patent, and is used in accordance with the license granted to Pinterest under our
Pinterest Canvas (“Pinterest Canvas”) is a family of multimodal foundation models that powers Pinterest experiences by enabling the enhancement of images. Pinterest Canvas has been trained on more than 600,000,000 data points, composed of publicly available Pins, Pin descriptions, and Pin metadata that Pinterest users have saved or uploaded to Pinterest, to which the users have granted Pinterest a license, as well as the continuous use of synthetic data. Training data rows may include one or more images together with text instructions and a target image. The data in the datasets were collected by Pinterest as early as 2009 and were first used in the development of Pinterest Canvas in or around January 2023. The data collection is ongoing. The datasets were cleansed, processed, and modified for quality purposes and to meet our trust, safety, and other internal standards.
Public content on the platform may be protected under copyright, trademark, or patent, and is used in accordance with the license granted to Pinterest under our
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