Grellas Shah LLP Partner Warns Of AI Trade Secret Risks
A recent federal trade secrets case highlights the risks of AI misappropriation, according to Crunchbase News. Companies must protect themselves from employees using AI to exploit trade secrets.
Original reporting · news.crunchbase.com
Original: “Protecting Trade Secrets In The Age Of AI”
Read “Protecting Trade Secrets In The Age Of AI” at Crunchbase News →
How this was written. Hustle Bucks wrote this article with a language model from Crunchbase News’s reporting (model: @cf/meta/llama-3.3-70b-instruct-fp8-fast); it describes that reporting rather than adding to it. The original, linked above, is the full story.
Key points from Crunchbase News’s report
- AI poses a significant threat to trade secrets, allowing employees to exploit proprietary information and gain an unfair advantage.
- Companies must implement strict AI policies and controls to protect their trade secrets from being misappropriated.
- Traditional methods of investigating trade secret theft are no longer effective, and companies must adapt to the new reality of AI-driven risks.
Crunchbase News reported a significant threat to companies' trade secrets in the age of AI. Employees with limited experience can now use AI to gain an unfair advantage, posing a risk to their former employers.
A case litigated by Seth Kugler, a partner at Grellas Shah LLP, involved a former senior employee who used stolen trade secrets to train an AI agent. This allowed the employee to create a competing business, leveraging the AI agent's capabilities.
AI is creating new ways for trade secrets to be misappropriated, going beyond traditional methods of theft. This new reality exposes companies to unprecedented risks, including the use of personal devices and AI agents to exploit trade secrets.
Key lessons for founders include the irreversibility of AI contamination. Once a trade secret is used to develop a machine learning model or train an AI agent, it can be difficult to undo the damage, even if the original files are deleted.
Personal devices can pose significant risks, as employees may inadvertently violate confidentiality agreements by running AI agents on their personal laptops. This can lead to trade secrets being disseminated outside the company, potentially losing legal protection.
Traditional digital discovery methods are no longer sufficient to investigate trade secret theft. AI tools can disperse, alter, and recreate data, making it challenging to detect and prove theft.
Companies can take proactive steps to protect their trade secrets, including implementing strict AI policies and eliminating remote access from unmanaged devices. They should also rewrite their confidentiality agreements to address AI use and model training inputs.
Questions and answers
What is the risk of AI contamination?
AI contamination can be difficult to undo, even if the original files are deleted, as it can irreversibly alter machine learning models or AI agents.
How can companies protect themselves from AI-driven trade secret risks?
Companies can implement strict AI policies, eliminate remote access from unmanaged devices, and rewrite their confidentiality agreements to address AI use and model training inputs.
What is the impact of personal devices on trade secret protection?
Personal devices can pose significant risks, as employees may inadvertently violate confidentiality agreements by running AI agents on their personal laptops, potentially disseminating trade secrets outside the company.
