No Rewind Button: Legal Pitfalls in Machine Learning Systems
Recognize the IP risks that arise as artificial intelligence and machine learning take a greater foothold in your business. Our three-part seminar will present solutions to risks that are unique to AI/ML, including:
- Protecting against copyright and other IP claims that may attach to AI/ML inputs, models, and outputs;
- Navigating IP and privacy considerations for AI systems implemented in edge computing and peripheral devices; and
- Establishing and enforcing trade secret protection of AI/ML development.
Machine learning systems present unique legal challenges because data that is ingested into those models often cannot be removed. If your model is tainted with ill-gotten data (from IP misappropriation, contract violations, etc.), it may be impossible to comply with court orders to remove the offending data. Learn to identify legal pitfalls in creating machine learning models and best practices for minimizing legal exposure from tainted data in these ML systems.
Moderator: Steven C. Carlson; Partner, Robins Kaplan LLP
Panelists: Roger Bodamer; Co-Founder/CTO/COO, Archipelago Analytics, and Dr. Mike Meehan; General Counsel and Chief Legal Officer, Diveplane
For executives and in-house counsel at companies embracing AI/ML, this complimentary three-part Minimum Continuing Legal Education course will empower you to stay ahead of the developing legal landscape.