A Lawyer’s Guide to AI: Ten Essential Concepts
Failed to add items
Add to basket failed.
Add to wishlist failed.
Remove from wishlist failed.
Adding to library failed
Follow podcast failed
Unfollow podcast failed
A Lawyer’s Guide to AI: Ten Essential Concepts
-
Narrated by:
-
By:
In this episode of The SciTech Lawyer Perspective, American Arbitration Association Commercial Vice President Aaron Gothelf interviews ABA Science & Technology Law Section's Chair-Elect, Matt Henshon to discuss his new book, “A Lawyer's Guide to AI: Ten Essential Concepts.” The conversation traces AI’s development from early predictive models to modern generative tools, emphasizing the role of data, pattern recognition, and prediction. Matt examines what distinguishes generative AI from earlier forms of machine learning, how data quality shapes AI outcomes, and why challenges such as overfitting and opacity pose problems for AI users. From a legal perspective, the episode examines algorithmic accountability, the adequacy of existing legal frameworks, and the issues lawyers and policymakers should be paying the closest attention to.