Advising on AI: Guiding Your Clients Through AI Challenges

This presentation will cover an overview of AI legal issues and risk management, including an overview of AI issues in current litigations and regulatory enforcements. It will cover current AI policy and legislation, including a discussion of the White House Executive Order on AI and a summary of some pending and recently passed AI legislation. It will conclude with specific steps companies need to take to manage AI legal risks including creating AI governance committees and developing role-based corporate AI policies.

Topics covered include:

Artificial Intelligence (AI) Business Law Intellectual Property Legal Tech

Agenda:

Overview of AI Issues and Risk Management
- Brief introduction of the presenter
- Summary of topics to be covered and anticipated takeaways
Overview of Current Litigation
- Copyright cases – infringement and fair use
- Open-source AI code generators
- Regulatory enforcements
AI Policy and Legislation
- White House executive order on AI
- AI legislation update
Managing AI Legal Risk
- AI governance committees
- Developing role-based corporate AI policies
Questions & Answers

Duration of this webinar: 60 minutes

Originally broadcast: September 19, 2024 10:00 AM PT

Webinar Highlights

This webinar is divided into section summaries, which you can scan for key points and then dive into the sections that interest you the most.

00:00 Introduction

James Gatto, the speaker, is an expert in AI legal issues with extensive experience and a role in academia. James outlines the webinar's focus on AI legal issues, policy, and risk management, noting the complexity of AI's legal landscape. He explains that legal issues vary based on a company's role in the AI ecosystem, such as data providers, model trainers, or tool developers. James emphasizes the importance of understanding a company's specific use of AI to effectively manage legal risks.

05:27 AI Legal Issues and Risk Management

James highlights the diversity of AI tools, including generative AI, chatbots, and high-risk decision tools, each with unique legal implications. Algorithmic discouragement is introduced as a significant risk, where improper data use can lead to costly penalties. James explains that generative AI outputs are typically not copyrightable, emphasizing the need for companies to understand copyright implications. He warns of the risks associated with employees using AI tools without company policies, potentially leading to confidentiality breaches. James stresses the importance of vendor diligence and the need for companies to develop policies to manage AI-related risks. He notes the increasing number of state laws regulating AI, with examples from Utah and Colorado, highlighting the evolving legal landscape.

14:56 Intellectual Property and Data Concerns

James elaborates on the EU AI Act and its potential extraterritorial effects on companies using AI. He explains the copyright office's stance that generative AI outputs are not protectable, emphasizing the need for human authorship. Patent laws remain unchanged, allowing AI-assisted inventions if there is significant human contribution. James discusses the importance of understanding AI tool terms of service, particularly regarding data retention and licensing. He highlights the potential liability for both tool providers and users if AI-generated content infringes on copyrights. James stresses the need for companies to update open-source policies to address AI code generators and manage legal risks. He mentions the EEOC's enforcement actions against biased AI tools in employment decisions, underscoring the importance of vendor diligence. James notes ongoing litigation related to AI, focusing on copyright infringement and the fair use defense.

38:49 Regulatory Landscape and Compliance

James discusses the potential for users of AI tools to face lawsuits once infringement findings occur. He highlights the FTC's active role in regulating AI, focusing on privacy, accuracy, and non-discrimination. The FTC's investigation into OpenAI is mentioned, emphasizing the importance of having reasonable policies in place. James explains the legal implications of using biometric information without authorization, citing the FTC's actions against Amazon. He stresses the importance of understanding data acquisition rights, particularly in relation to training AI models. James provides a cautionary tale of Everalbum, a company that faced FTC enforcement for improper data use in AI training. He notes the involvement of various regulatory bodies, such as the SEC, FCC, DOT, and FDA, in AI-related issues. James outlines the White House executive order on AI, which mandates actions from federal agencies to promote responsible AI use.

52:43 AI Governance and Policy Development

James emphasizes the need for companies to develop AI policies and governance structures tailored to their specific roles and activities. He advises forming an AI governance committee with representatives from various departments to ensure comprehensive policy development. Education and training are crucial for understanding legal and business implications, enabling effective policy formulation. James highlights the importance of vendor diligence, especially when integrating AI features into existing tools. He stresses the need for companies to conduct data mapping and assess legal risks before investing in AI training. James advises companies to ensure compliance with AI regulations and ethical standards through role-based policies and enforcement mechanisms. He notes the significance of understanding the evolving regulatory landscape and adapting policies accordingly.

01:01:36 Q&A and Closing Remarks

James addresses audience questions, emphasizing the importance of data rights and managing open-source outputs in AI training. He highlights the need for fact-checking AI outputs to avoid defamation and other legal issues. James stresses the importance of disclosure and transparency, particularly in consumer interactions involving AI. He advises on forming AI governance committees with diverse representation to address legal, technical, and business aspects. James underscores the need for training and enforcement mechanisms to ensure compliance with AI policies. He discusses the balance between innovation and compliance, emphasizing the importance of understanding regulatory challenges.

Please note this AI-generated summary provides a general overview of the webinar but may not capture all details, nuances, or the exact words of the speaker. For complete accuracy, please refer to the original webinar recording.

Continuing Legal Education (CLE) Credits

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California CLE

Status: Approved

Credits: 1.00 General

Earn Credit Until: June 30, 2026

South Carolina CLE

Status: Approved

Credits: 1.00 General

Difficulty: All Levels

Earn Credit Until: December 31, 2025

North Carolina CLE

Status: Approved

Credits: 1.00 General

Earn Credit Until: February 28, 2026

Texas CLE

Status: Approved

Credits: 1.00 General

Earn Credit Until: August 31, 2025

This presentation is approved for one hour of General CLE credit in California, South Carolina (all levels), and North Carolina. This course has been approved for Minimum Continuing Legal Education credit by the State Bar of Texas Committee on MCLE in the amount of 1.00 credit hours.

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Speaker

James Gatto AI Team Leader
Sheppard Mullin

Jim Gatto is a partner in the Intellectual Property Practice Group in the firm’s Washington, D.C. office. He is Co-Leader of the Artificial Intelligence Team, the Blockchain & Fintech Team, and Leader of the Open Source Team. Read More ›

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