Goldberg Segalla partner Frank Ramos authored an article on defending AI-embedded products, published by the Claims and Litigation Management Alliance (CLM), a national organization for professionals in the risk, claims, and litigation management industries.

A recognized AI thought leader and advocate for the ethical adoption of AI in the legal field, Frank’s article, “The Black Box on Trial,” explores how machine‑learning systems that cannot explain their own decisions are challenging traditional product liability law.

He opens with the “black box problem,” where complex AI systems, such as self-driving cars or medical diagnostics, can describe what decision they made, but not why. These systems rely on neural networks trained on massive datasets, making their reasoning opaque even to their creators. As AI becomes increasingly embedded in consumer products, this lack of transparency is emerging as a central issue when harm occurs and juries expect clear explanations.

“No engineer designed those weights by hand, and no programmer wrote an if-then rule that said run the red light,” Frank writes. “The system taught itself, and the reasoning behind its decision is embedded in a mathematical structure that no human can fully interpret. That is the black box problem, and it is about to become the central challenge in product liability litigation.”

Frank explains that traditional product liability doctrines struggle to adapt because they were built for products whose mechanisms can be understood and traced. By contrast, AI outputs are the result of complex and often inscrutable mathematical processes, creating a structural advantage for plaintiffs.

“Plaintiffs are beginning to argue that the inability to explain an AI system’s decision-making process is itself a design defect,” Frank says. “The theory runs like this: A manufacturer that deploys a product capable of autonomous decision-making but incapable of explaining those decisions has designed a product that is unreasonably dangerous because it cannot be monitored, audited, or corrected in real time.”

While Frank acknowledges that this theory has “real teeth,” he emphasizes that defense counsel must confront it directly by highlighting the tradeoffs between explainability and performance.

“The response is not that black-box models are safe,” he begins. “The response is that interpretable models are not always available, and when they are, they often sacrifice the accuracy and performance that make the product effective in the first place.”

Frank concludes that this tension will shape the future of AI litigation.

“AI product liability law is being written right now in courtrooms, not in law-review articles, he says. “The first generation of verdicts will establish the principles that govern this field for decades. Defense counsel who understand the technology, can explain black-box decision-making in terms a jury can grasp, and can present the engineering tradeoffs honestly and persuasively, will win cases that less-prepared lawyers will lose.”

READ THE FULL ARTICLE HERE (Subscription Required): “The Black Box on Trial” CLM, June 10, 2026

MORE ABOUT GOLDBERG SEGALLA’S FRANK RAMOS:

Frank is a nationally recognized legal advisor and litigator who focuses his practice on retail, product liability, premises liability, trucking, insurance and commercial disputes. He has been defending clients in civil litigation for more than 26 years and has taken numerous trials and arbitrations to verdict or award.

Frank uses his extensive litigation experience to provide counsel, defense, and strategic guidance to retailers, developers, restaurants, fitness chains, hotels, resorts and other hospitality businesses. His representation has included negligent security, slip/trip and falls, catastrophic personal injury, trucking and motor vehicle accidents, employment and construction claims, as well as a variety of commercial disputes ranging from intellectual property and breach of contract to bad faith, franchise agreements, and landlord-tenant issues.