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.

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.

Session I | No Rewind Button: Legal Pitfalls in Machine Learning Systems

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

Dr. Mike Meehan
General Counsel and Chief Legal Officer
Diveplane

CLE Accreditation

Robins Kaplan LLP will seek approval with the Mandatory Continuing Legal Education Board in Minnesota for 1.0 hour of standard credit for each session. The Berkeley Center for Law & Technology will seek approval with the Minimum Continuing Legal Education Board in California for 1.0 credit hour for each session.

Questions? Contact Christine Berndt at
CBerndt@RobinsKaplan.com or 612.349.8404.