Second Annual AI Legal Summit

Hosted by Robins Kaplan LLP and Berkeley Center for Law & Technology

May 5, 12, and 19, 2021


David A. Prange


Deputy Chair, IP and Technology Litigation Group

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

Wednesday, May 5, 2021 | 11:00 a.m. – 12:00 p.m. PT

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.


Steven C. Carlson
Robins Kaplan LLP


Roger Bodamer
Archipelago Analytics

Dr. Mike Meehan
General Counsel and Chief Legal Officer

Session II | AI on the Edge: Legal Considerations for Artificial Intelligence Systems from Peripheral Devices

Wednesday, May 12, 2021 | 11:00 a.m. – 12:00 p.m. PT

Artificial intelligence power is increasingly being pushed to the edge of computing systems, such as hand-held devices and household appliances. Edge AI moves interaction as close to the user as possible by processing data locally, in real time, disconnected from the cloud. This architecture increases performance and responsiveness to the end user. However, collecting data and running AI more broadly through edge devices triggers new legal exposures, particularly with security, privacy, and licensing. Learn how courts and the patent office will treat Edge AI inventions, what constitutes a reasonable security measure in an Edge AI system, and what additional privacy risks exist.


Kevin M. Pasquinelli
Robins Kaplan LLP 


Deepak Dutt

Michael D. Reif
Robins Kaplan LLP

Session III | Trade Secret as a Mechanism for Protecting AI/ML Development

Wednesday, May 19, 2021 | 11:00 a.m. – 12:00 p.m. PT

When investing in artificial intelligence and machine learning process and algorithm innovation, one should consider how to protect that investment from misappropriation. In this presentation, learn to identify, define, and capture those components of your AI/ML development process and training data that are distinguishable from shared advancements in the field.


David A. Prange
Robins Kaplan LLP


Bradley D. Baugh
North Weber & Baugh LLP

Aaron Brodsky
Chief Intellectual Property Counsel
Trimble Inc

Antony Craggs
Lewis Silkin LLP

Thomas Gaunt
Lewis Silkin LLP

Chris Hilberg
Senior Director, Legal
Best Buy

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 or 612.349.8404.

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Patent Value: Scoring Patents Using Characteristics Of Patents In Litigation
Christopher K. Larus, Miles A. Finn, Congnan Zhan, Joseph (Yu) Chen, and Shelley Gilliss - les Nouvelles
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Trade Dress Through a Trial Lens: Six Strategy Tips For Litigants
Christopher Larus, William Manske - Managing IP
August 25, 2022

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