Machine Learning Integration Into Your Company: What IP Considerations Exist?

Machine learning has become a huge hot topic both in and out of the tech world. Even the companies that are not actively hiring AI engineers may still be using AI products, such as ChatGPT. Incorporating AI into company workflows, whether you're building your own models or borrowing someone else's, will invite new types of intellectual property issues. This program, presented by Elliot Karlin, will provide you with a basic understanding of machine learning systems and introduce intellectual property issues that can arise from integrating machine learning into a company's workflow.

This program will include:

• A breakdown of machine learning:

• • How does machine learning work?

  • How are machine learning models trained?

  • What can a machine learning model create?

• What are the trade secret implications in using an external machine learning model:

• • What does trade secret protect?

  • What happens when a trade secret is input into a machine learning model?

  • What can you do to protect your trade secrets?

• What are the copyright implications in training an internal machine learning model:

• • What does copyright protect?

  • Where in machine learning process would copyright infringement occur?

  • What can you do to minimize risk when internally training machine learning models?

Learning Objectives:

1. Review the general functioning of a machine learning system 

2. Generate internal procedures for working with external models 

3. Identify internal procedures for training internal models