Apple warns of clawback of trade secrets given to AI
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| Source: Mastodon | Original article
Apple warns that trade secrets fed into AI systems could be reclaimed, raising legal and security concerns.
Apple has taken a fresh legal step in its ongoing dispute with OpenAI, filing a Monday motion that warns of “irreversible” damage when proprietary information is fed into a generative‑AI system. The filing argues that trade secrets embedded in an AI model cannot be cleanly removed, raising the prospect that once such data are incorporated they may persist indefinitely in the model’s weights and outputs.
The move builds on Apple’s earlier accusations that OpenAI destroyed evidence, which we reported on 2 September. In the new filing Apple asks a federal judge to reject OpenAI’s motion to dismiss the trade‑secret lawsuit, contending that the defense rests on “distortion, speculation, and …” a misunderstanding of how AI learning works. Apple’s concern is that the company’s confidential designs and processes, allegedly supplied by former Apple staff now at OpenAI, could be reproduced by the AI, undermining Apple’s competitive edge.
OpenAI has responded with a counter‑filing that denies the allegations and frames its recruitment of former Apple personnel as legitimate. The firm also argues that Apple’s own security and off‑boarding practices, which allowed a manager to retain access to internal data, weaken Apple’s case. In a separate filing, OpenAI claims that Apple’s internal safeguards contributed to the alleged leakage.
Why it matters is twofold: first, the case could set a precedent for how trade secrets are protected—or not—when they become part of a machine‑learning model. Second, it spotlights the broader industry challenge of “unlearning” data from AI systems, a technical hurdle that regulators and companies are only beginning to grapple with.
The next key moment will be the judge’s ruling on OpenAI’s motion to dismiss. A decision to let the case proceed could lead to a deeper examination of AI‑training data provenance, while a dismissal might embolden firms to rely on similar recruitment practices. Stakeholders will also be watching for any settlement talks or further court‑ordered disclosures that could clarify how trade secrets are to be handled in the age of large language models.
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