Benefits Of And Best Practices For Protecting Artificial Intelligence And Machine Learning Inventions As Trade Secrets

• Published date: 16 February 2022
• Subject Matter: Intellectual Property, Patent, Trade Secrets
• Law Firm: Mintz
• Author: Ms Marguerite McConihe and Meena Seralathan

We previously discussed which portions of an artificial intelligence/machine-learning ('AI/ML') platform can be patented. Under what circumstances, however, is it best to keep at least a portion of the platform a trade secret? And what are some best practices for protecting trade secrets? In this post, we explore important considerations and essential business practices to keep in mind when working to protect the value of trade secrets specific to AI/ML platforms, as well as the pros and cons of trade secret versus patent protection.

Protecting AI/ML Platforms via Trade Secrets

What qualifies as a 'trade secret' can be extraordinarily broad, depending on the relevant jurisdiction, as, generally speaking, a trade secret is information that is kept confidential and derives value from being kept confidential. This can potentially include anything from customer lists to algorithms. In order to remain a trade secret, however, the owner of the information must follow specific business practices to ensure the information remains secret. If businesses do not follow the proscribed practices, then the ability to protect the trade secret is waived and its associated value is irretrievably lost. The business practices required are not onerous or complex, and we will discuss these below, but many businesses are unaware of what is required for their specific type of IP and only discover their error when attempting to monetize their inventions or sell their business. To avoid this devastating outcome, we work to arm our clients with the requisite practices and procedures tailored to their specific inventions and relevant markets.

In the context of AI/ML platforms, trade secrets can include the structure of the AI/ML model, formulas used in the model, proprietary training data, a particular method of using the AI/ML model, any output calculated by the AI/ML model that is subsequently converted into an end product for a customer, and similar aspects of the platform. There are myriad ways in which the value of the trade secret may be compromised.

For example, if an AI/ML model is sold as a platform and the platform provides the raw output of the model and a set of training data to the customer, then the raw output and the set of training data would no longer qualify for trade secret protection. Businesses can easily avoid this pitfall by having legally binding agreements in place between the parties to protect the confidentiality and ownership interests involved. Another area in which we frequently see companies waive trade secret protection is where the confidential information that can be independently discovered (such as through reverse-engineering a product). Again, there are practices that businesses can follow to avoid waiving trade secret protection due to reverse-engineering. Owners, therefore, must also be careful in ensuring that the information they seek to protect cannot be discovered through use or examination of the product...