Apple’s “privacy-first” AI meets a copyright fight: what India should watch
If you thought the AI copyright wars were yesterday’s news, Apple just dragged them back to center stage. On October 10 (late night IST), two neuroscientists sued Apple in a California court, alleging the company trained “Apple Intelligence” on pirated copies of their books. It’s the second such suit against Apple in as many months, and it lands right when Apple Intelligence is rolling out more widely—including in India.
Translation: we’re about to find out whether “privacy-first AI” and messy data pipelines can peaceably coexist. Spoiler: not without lawyers.
What exactly is Apple accused of?
The new case, filed by SUNY professors Susana Martinez-Conde and Stephen Macknik, alleges Apple used “shadow libraries” of pirated books to train Apple Intelligence. They say two of their titles—Sleights of Mind and Champions of Illusion—are in those datasets. The suit seeks damages and a court order to stop any further use of their works. Apple hasn’t commented yet.
This stacks on top of a September complaint by authors Grady Hendrix and Jennifer Roberson, which also alleges Apple’s models were trained on Books3 (a trove of scraped/pirated books used in several open datasets) and other “shadow libraries.”
If those datasets sound familiar, it’s because they’ve been name-checked in AI lawsuits against other tech players. In August, Anthropic agreed to a $1.5 billion settlement with authors—raising the stakes across the industry.
Plaintiffs say Apple’s training data crossed legal lines; Apple, for now, is silent publicly.
Why this case matters beyond Apple
Apple Intelligence is the company’s big bet: system-level AI across iPhone, iPad, and Mac with a heavy privacy pitch (“on-device” processing and something Apple calls Private Cloud Compute). That branding is rock solid with consumers—but it doesn’t immunize the training stage from copyright claims.
Two threads make this case consequential:
· Legal momentum: U.S. courts are letting major copyright cases against AI firms proceed. Rulings aren’t uniform, but plaintiffs keep clearing early hurdles. That pressures companies to prove (or fix) their data supply chains.
· Precedent risk: A big loss or settlement could reshape how AI models are trained—forcing more expensive licensing, opt-out/opt-in mechanisms, or narrower datasets. Costs roll downhill to users.
whatever happens to Apple will influence what other AI providers do next.
The India angle: what changes for users, authors, and publishers
First, availability. Apple Intelligence is live in India on supported devices (iPhone 15 Pro/Pro Max and newer Pro-class devices; Macs and iPads with Apple silicon), with features and languages expanding over 2025. Some capabilities are region/language-limited, so check Apple’s India pages and feature-availability notes.
For Indian rights holders, this lawsuit lands amid India’s own AI-copyright churn:
· No explicit TDM exception (yet): India’s Copyright Act doesn’t have a clear text-and-data-mining carve-out; parties lean on Section 52 “fair dealing,” which is narrower than the EU/UK TDM regimes. Policymakers are studying reforms.
· Active litigation climate: Indian publishers and media houses are already in court with OpenAI over training and outputs, and the government has convened an expert panel to review copyright law for the AI era. Expect any Apple outcome in the U.S. to echo in Indian pleadings and policy notes.
Practical impact for Indian users today? Minimal—features won’t disappear overnight because of an American lawsuit. But mid-term, a precedent that forces paid licensing or dataset purges could slow feature rollouts, limit generative options, or nudge prices upward for AI-enhanced services. That’s particularly relevant as Apple widens language support and India-specific experiences.
What experts disagree on
· Is training on copyrighted text “fair use” (or Indian “fair dealing”)? U.S. cases are split and context-heavy; India has even less clarity and no statutory TDM lane. Companies argue training is transformative and non-substitutive; rights holders argue large-scale copying is still copying. (Expect divergent court outcomes before any equilibrium emerges.)
· Does a “privacy-first” runtime absolve training-time copying? Apple’s on-device/secure cloud story is about user data, not training data. Plaintiffs say reputational privacy doesn’t license pirated corpora. Apple’s legal answer (when it comes) will likely separate the two.
One-liner: India’s courts and ministries are watching; any clear U.S. precedent will be cited in Delhi filings within days.
What Apple Intelligence is (and isn’t) right now
For context: Apple Intelligence is a bundle of writing tools, image features (Genmoji/Image Playground), smarter Siri, and “visual intelligence,” with some features in beta and language/region caveats. Apple keeps adding languages and polishing availability claims after ad-industry scrutiny. Indian users can already access a subset, with more slated through OS updates.
Summary: promising features, staggered rollout, lots of footnotes.
Pros and cons (from an India user/industry lens)
Pros
· System-level AI with strong on-device processing story; potentially better privacy posture at runtime.
· Growing India availability and language support as of 2025 updates.
· Could pressure industry to clean up training-data supply chains—good for Indian authors if licensing normalizes.
Cons
· Legal uncertainty around training data could slow features or reshape costs passed to consumers.
· India’s own law is in flux; rights holders lack a crisp TDM pathway today.
· Feature fragmentation by region/language remains, despite expansions.
If you’re an Indian author or publisher, keep records of your catalog’s inclusion in datasets and watch U.S. dockets; if you’re a user, expect features to keep coming—but with more legal fine print.
Risks and unknowns
· Apple’s defense: Unknown. The company hasn’t publicly detailed training data sources for Apple Intelligence or commented on these specific claims.
· Dataset provenance: Whether Books3/shadow libraries were used—and how—is for discovery to reveal. Prior suits against other firms suggest such corpora were widely circulated in open-model pipelines.
· Policy swing in India: A panel review is underway, but no timeline for statutory changes. Reforms could either open a narrow TDM safe harbor or double down on licensing.
The sensible bet: more licensing deals and stricter dataset hygiene across big AI platforms, Apple included.
The upshot: Apple being sued over alleged use of copyrighted books doesn’t change your iPhone today, but it could shape how fast—and on what terms—AI shows up in India tomorrow. We’ll update this piece when Apple or the court clarifies the record.