“With great power comes great responsibility,” and in the rapidly evolving landscape of Artificial Intelligence (“AI”), the intersection of innovation and legal responsibility is becoming increasingly complex. As AI becomes more integrated into products and services across industries, matters regarding liability, regulation, and safety are raising questions about the tension between AI and liability. Courts must apply existing legal frameworks to this emerging technology while lawmakers play catch up and enact guardrails to ensure its safe and lawful use. This article explores the implications of AI in the context of product liability, focusing on recent litigation and potential theories of liability that companies must navigate as AI continues to permeate every sector of the economy.
The ‘Black Box’ Problem: What Makes AI Unique in Product Liability?
Like an airplane’s black box data which is typically undecipherable to non-experts, AI systems, particularly those powered by machine learning, are often described as “black boxes.” Unlike traditional products where design and functionality are relatively static and transparent, AI systems are dynamic and self-evolving. They learn and adapt based on vast datasets, making their decision-making processes opaque, even to their creators. AI’s fluidity raises critical questions for product liability, including whether an AI-generated model or system falls under the legal definition of a “product” for the purposes of liability claims, whether the AI’s developer, the company deploying it, or both, are subject to liability, and the scope of reasonably foreseeable risks and harms given that AI systems are self-designed to continuously evolve over time.
These questions are at the heart of ongoing litigation and legislative debates as courts and lawmakers grapple with how to apply traditional product liability frameworks to the ever-evolving AI landscape.
Recent Cases: AI in the Product Liability World
A few recent cases illustrate the legal challenges presented by artificial intelligence. In one case filed in Los Angeles Superior Court, plaintiffs allege that the AI-driven algorithms on various websites caused mental health harms, including addiction, anxiety, depression, and even suicide among minors. This litigation highlights that AI systems designed to maximize user engagement are now being alleged to exploit psychological vulnerabilities, especially in adolescents. Plaintiffs argue that these platforms are defectively designed and lack adequate warnings about their risks, making them unreasonably dangerous for minors.
The emergent application of product liability claims to AI systems is further exemplified in a case in the U.S. District Court for the Middle District of Florida, where the parent of a deceased child filed suit, alleging that an AI chatbot platform caused the wrongful death of her fourteen-year-old son. The plaintiff alleged that the chatbot engaged the minor in hypersexualized and manipulative conversations, ultimately leading to his suicide. The plaintiff brought counts of failure to warn and defective design, among others, raising questions about whether AI chatbots can be considered “products” for the purposes of product liability and whether their developers have a duty to warn users about foreseeable harms. This case highlights the unique challenges of AI product liability, including whether data sets used by AI platforms can be considered design flaws and whether the company had a duty and breached its duty to warn users about the dangers of its AI system, especially for children.
Theories of Liability: Design Defect, Failure to Warn, and Beyond
Traditional product liability theories—design defect, manufacturing defect, and failure to warn—are being tested in the context of AI. For example, with regard to design defects, if an AI system is alleged to cause harm due to its design facilitating biased decision-making or unsafe recommendations, can the developer be held liable? What will the evolution of design defect cases look like if the design of the AI product itself (assuming it is a “product”) is constantly changing, and will that evolution impact product liability litigation in other industries? Will the scope of design defect claims narrow or widen? For failure to warn claims, do companies have a duty to warn users about the limitations and risks of their AI systems, such as the potential for addiction or misuse? What are the reasonably foreseeable risks of using AI? What really is the “intended use” of AI? And concerning negligence, can a company be found negligent for failing to adequately test or monitor an AI system? If AI is available to anyone who has access to the internet, are there any constraints on a negligence claim? These theories are complicated by the “black box” nature of AI, which may make it difficult to pinpoint the cause of harm or assign responsibility. As AI becomes more ubiquitous, litigation involving claims of injury, wrongful death, and other harms allegedly caused by AI systems will inevitably loom large.
Looking Ahead: What You Need to Know
As AI continues to evolve, so, too, will the legal and regulatory landscape. Companies developing or deploying AI systems should take proactive steps to mitigate liability risks, which may include:
- Conducting Bias Audits: Regularly test AI systems for bias and disparate impact, as required by laws like New York City’s Automated Employment Decision Tools law.
- Implementing Transparency Measures: Disclose to customers how the company’s AI systems work, what data they use, and what risks they pose.
- Monitoring Legislative Developments: Stay informed about state and federal AI laws, which are continuously evolving. For a comprehensive overview of state AI legislation and the status of AI-related bills across the country, visit the Husch Blackwell AI State Law Tracker.
- Engaging Legal Counsel: Work with experienced attorneys to navigate the complex intersection of AI and product liability.
AI is a transformative technology that presents unprecedented legal challenges. As courts, lawmakers, and regulators grapple with the “black box” of AI, companies must be vigilant in understanding and addressing their liability risks.
For more information from the HB AI team, visit AI Attorneys | Husch Blackwell.