In this clip from AI Contracts Explained, our panel unpacks the growing complexity of data handling in AI contracts. Shannon Yavorsky, Kate Aishton, and Laura Frederick discuss why data use diligence is so critical. They explore increased scrutiny around anonymized data and how synthetic data creates new legal and business risks. The conversation also addresses data subject rights in AI tools and how the definition of personal data is expanding beyond traditional identifiers.
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Watch AI Contracts ExplainedĀ Training Episodes
Every Friday, How to Contract brings to you a new episode of AI Contracts Explained. This series is designed to help lawyers and contract teams who already know SaaS and software contracts learn what they need to know to work on contracts for products with AI features.Ā Each episode will feature AI contract experts doing a deep dive into the practical realities lawyers and contract teams need to know.
Learn more about the AI Contracts Explained training series
Watch these short training videos
What Can Your AI Vendor Do With Your Data?
What Are You Promising in Your AI Contracts?
In this clip from AI Contracts Explained, our panel of speakers dives into warranties found in AI contracts. Will Dugoni, Olga Mack, John Pavolotsky, and Laura Frederick explore the importance of warranties, typical customer and vendor negotiation strategies, and what we can expect in the future.Ā
Who Owns an AI Product'sĀ Output?
Tiffany Bui LeTourneau dives into who owns what AI creates. While many AI programs say users own their creations, the real question is can you? Tiffany shares a recent U.S. Copyright Office ruling where AI-generated images didn't get copyright protection due to insufficient human authorship and unpredictable results. Tiffany wraps up by urging companies using AI in code generation to think about protecting their products.
Why Accuracy Is a Challenge With AI Contracts
Amanda MercedĀ discusses the challenges people face with AI use cases, particularly around understanding risk and accuracy. Amanda highlights how AI often enhances services similar to human capabilities, aiming to make quicker decisions or replace human roles. The tension in negotiations about accuracy levels between AI companies, who see themselves as just software, and customers who expect AI to match human precision.Ā
Responding to "You Can't Use My Data With AI"
In this quick video,Ā Kevin Keller (dressed as Ebeneezer Scrooge) discusses how to respond to customers who object to their data being used with AI. He emphasizes the need for a compromise and suggests negotiating terms to ensure data can be used responsibly, such as de-identifying data to improve AI models. This approach aims to enhance services and achieve higher accuracy while addressing customer concerns.
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