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OpenAI Told to Hand Over Hiring Records in Apple Secrets Case

OpenAI Told to Hand Over Hiring Records in Apple Secrets Case

A US court has ordered OpenAI to turn over recruitment records and interview materials in a trade secrets lawsuit filed by Apple. The ruling sets a tight schedule: OpenAI must deliver the first batch of documents within five days and the remaining requested files within fourteen days.

The discovery covers interview documents related to former Apple employees who now work in OpenAI’s consumer hardware and robotics divisions. That includes interview checklists, explanatory notes, technical presentation slides, and LINE messaging records. The court also approved discovery for OpenAI employees Liu Chang, Peng Ailisa, and Chief Hardware Officer Tang Yaotan.

Apple’s complaint alleges that former employees used company laptops to download confidential materials, including unpublished technical specifications and proprietary project data. The lawsuit lands as OpenAI pushes deeper into consumer hardware—a market currently dominated by smartphones.

At its core, the case is about where talent recruitment ends and trade secret misappropriation begins. How the court draws that line could influence talent mobility across the tech industry and sharpen the rules companies use to protect their intellectual property.

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Key Points

  • Court order: OpenAI must submit hiring records and interview materials; first batch due in 5 days, remainder in 14 days.
  • Scope: Documents cover former Apple employees now in OpenAI’s consumer hardware and robotics teams, including interview checklists, technical slides, and LINE messages.
  • Named individuals: Discovery extends to Liu Chang, Peng Ailisa, and Chief Hardware Officer Tang Yaotan.
  • Apple’s claim: Ex-employees allegedly downloaded confidential files, including unpublished specs and project data, using company laptops.
  • Broader impact: The case tests the boundary between recruitment and trade secret protection, with potential consequences for talent movement in the AI hardware race.