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Apple says it trained its generative AI systems on a mix of publicly available material, licensed or purchased data, open-source datasets, user-study data, and synthetic content. But its public disclosures do not identify every work or creator in the training material, so they cannot show whether a particular artist’s work was included or what permission applied to it.
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What data does Apple say it used?
In a disclosure dated September 9, 2026, Apple says its generative-AI training data includes trillions of individual data points. That is Apple’s description of the overall scale—not a count of artworks, images, or creators. Apple lists five broad sources:
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- Licensed or purchased third-party data: material Apple says it obtained from other providers.
- Open-source datasets.
- User-study data.
- Synthetic data: content generated to supplement real-world datasets and also used in post-training.
Apple says its datasets include public-domain material as well as material subject to intellectual-property rights. It says some data is licensed directly or available under licenses that permit its use in generative-AI development. Those statements describe categories and approaches; they do not establish the legal status or permission terms for every item. Apple’s dataset disclosure does not provide a complete work-by-work list linking material to an artist, URL, or license.
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What controls does Apple describe for web data?
Apple says Applebot does not crawl sites that require login credentials or are protected by a paywall. It also says the crawler respects standard robots.txt directives, including directives that tell Apple not to use a website’s content for foundation-model training. These are Apple’s stated crawler policies; the cited disclosures are not an independent audit of what entered every training dataset.
Apple also describes filtering and processing public and crawled material. Its current disclosure lists safety, profanity, inappropriate-content, spam, financial-data, and quality filters; plain-text extraction; fuzzy deduplication; and checks to remove overlap with benchmark data. Apple says synthetic text, images, audio, and other content supplement real-world data and are used in post-training. Its 2024 foundation-model overview likewise described filtering low-quality material and removing personally identifiable information such as Social Security and credit-card numbers. These are descriptions of Apple’s process, not evidence of an external review.
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- KNOW YOUR SLEEP SCORE—With advanced sleep tracking, Series 11 gives you a daily sleep score. It’s an easy way to help measure and understand the quality of your sleep, so you can make it more restorative.
- GET HYPERTENSION NOTIFICATIONS—Did you know that Series 11 can spot signs of chronic high blood pressure? By analyzing how your blood vessels respond to beats of the heart, it can notify you of possible hypertension.*
- SAFETY FEATURES—A smartwatch that puts your safety first. Series 11 can detect a hard fall or severe car crash, automatically help connect you with emergency services, and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
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Did artists have a say?
The public information cited here does not answer that question for individual artists. Apple describes licensing and crawler controls, but it does not publish a complete inventory showing which works were used, who made them, or the terms under which each was obtained. Without that information, readers cannot determine from these disclosures whether a particular artist’s work was included, whether it was licensed, or whether a site-level control applied to it.
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In July 2024, artists and other creative-community members criticized Apple’s limited transparency about how it assembled training data. Vancouver-based video-game artist and creators’ rights activist Jon Lam told Engadget: “I wish Apple would have explained to the public in a more transparent way how they collected their training data.” Engadget reported Lam’s comment on July 3, 2024. The concern was about meaningful information on data sources; it should not be taken to mean all artists share one view or that Apple has acknowledged using any named artist’s work.
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- A FULL-FEATURED HEALTH TRACKER—Apple Watch Series 11 gives you invaluable insights about your body, right from your wrist. Take an ECG anytime* and get alerts for a high and low heart rate or an irregular rhythm*—so you can stay closer to your heart. You can also view your overnight health tracking metrics with the Vitals app* and be notified of possible sleep apnea.*
- KNOW YOUR SLEEP SCORE—With advanced sleep tracking, Series 11 gives you a daily sleep score. It’s an easy way to help measure and understand the quality of your sleep, so you can make it more restorative.
- GET HYPERTENSION NOTIFICATIONS—Did you know that Series 11 can spot signs of chronic high blood pressure? By analyzing how your blood vessels respond to beats of the heart, it can notify you of possible hypertension.*
- SAFETY FEATURES—A smartwatch that puts your safety first. Series 11 can detect a hard fall or severe car crash, automatically help connect you with emergency services, and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
- A POWERFUL FITNESS TRACKER—With advanced metrics and motivating features like Pacer, Heart Rate Zones, training load, and Workout Buddy powered by Apple Intelligence from your nearby iPhone*—Series 11 is made to help everyone stay active, from runners and hikers to strength-training enthusiasts.
What do Image Playground and Genmoji tell us?
Apple’s creative features make generative AI visible in everyday use, but they do not reveal training-data provenance. Apple introduced Image Playground and Genmoji among Apple Intelligence features in December 2024. Image Playground lets users create images from descriptions and concepts, and Apple says it can also use people from a photo library; the feature is integrated into apps including Messages, Freeform, and Keynote. Apple’s launch announcement describes the features, not the specific works used to train the underlying models.
For current access, Apple’s Image Playground iPhone support guide describes creation from text descriptions, selected styles, and photos or people in Photos. Eligibility depends on supported devices, operating systems, language, and region, and Apple notes that usage limits may apply. Those conditions can change, so consult the support guide for current availability. Feature access does not establish whether a particular artist’s work was in the training data.
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What can and cannot be concluded?
- Apple has disclosed broad source categories and some collection and processing controls. The disclosures distinguish public web material, licensed or purchased data, open-source datasets, user-study data, and synthetic content.
- Public availability is not the same as individual licensing or consent. Apple’s categories include both public-domain and rights-protected material, and the disclosure does not identify the status of each item.
- The scale figure is not a creative-work count. Apple’s “trillions of individual data points” statement does not say how many artworks or artists that represents.
- The cited sources do not establish an independent audit or a full inventory. They explain Apple’s stated practices, but do not resolve whether any particular artist’s work was used or under what terms.
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