By Justin Donoho
Duane Morris Takeaway: Available now is the recent article in the Journal of Robotics, Artificial Intelligence & Law by Justin Donoho entitled “Three Best Practices to Mitigate High-Stakes AI Litigation Risk.” The article is available here and is a must-read for corporate counsel.
Organizations using AI-based technologies that perform facial recognition or other facial analysis, website advertising, profiling, automated decision making, educational operations, clinical medicine, generative AI, and more increasingly face the risk of being targeted by class action lawsuits and government enforcement actions alleging that they improperly obtained, disclosed, and misused personal data of website visitors, employees, customers, students, patients, and others, or that they infringed copyrights, fixed prices, and more. These disputes often seek millions or billions of dollars against businesses of all sizes. This article identifies recent trends in such varied but similar AI litigation, draws common threads, and discusses three best practices that corporate counsel should consider to mitigate AI litigation risk: (1) add or update arbitration clauses to mitigate the risks of mass arbitration; (2) collaborate with information technology, cybersecurity, and risk/compliance departments and outside advisors to identify and manage AI risks; and (3) update notices to third parties and vendor agreements.
Implications For Corporations
Companies using AI technologies face multimillion- or billion-dollar risks of litigation seeking statutory and common-law damages under a wide variety of laws, including privacy statutes, wiretap statutes, unfair and deceptive practices statutes, antidiscrimination statutes, copyright statutes, antitrust statutes, common-law invasion of privacy, breach of contract, negligence, and more. This article analyzes litigation brought under these laws and offers corporate counsel three best practices to mitigate the risk of similar cases.