US judge partially grants Apple's expedited discovery motion, ordering OpenAI to produce forensic device images and documents
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| Source: Techmeme | Original article
A federal judge in California partially granted Apple’s request for expedited discovery, ordering OpenAI to provide forensic images of devices and related documents.
A U.S. district judge in California has granted Apple Inc. limited expedited discovery in its trade‑secret lawsuit against OpenAI Inc., compelling the AI firm to produce a range of internal materials. The ruling, issued by Judge Edward Davila on Oct. 13, 2026, orders OpenAI to hand over forensic images of devices used in the case, documents related to the interviewing of Apple job candidates, hiring records, and the testimony of selected OpenAI employees.
Apple’s suit, filed in July, alleges that former Apple staff who joined OpenAI took proprietary information about the iPhone maker’s AI initiatives. By securing forensic device copies and hiring data, Apple hopes to trace any alleged misappropriation and bolster its claim that OpenAI benefited from Apple’s confidential work.
The decision matters because it signals that courts are willing to accelerate discovery in high‑stakes AI disputes, where the underlying technology can be both complex and highly valuable. Access to device images and internal communications could give Apple a clearer picture of how OpenAI may have used its trade secrets, potentially shaping settlement talks or influencing a jury’s view if the case proceeds to trial. For OpenAI, the order adds operational pressure and raises concerns about protecting its own confidential data while complying with a broad subpoena.
The next steps will focus on how OpenAI responds to the discovery demands and whether the parties reach a settlement before a full trial. Observers will watch for additional rulings on the scope of permissible materials, any claims of privilege or confidentiality, and the broader impact on how AI companies safeguard and defend trade secrets in an increasingly competitive landscape.
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