March 29, 2019

Medical AI: Legal Issues of Robotics in Healthcare

Your pacemaker uses machine learning algorithms to detect irregularities in your breathing and make related predictions about the function of your heart. Although this allows for more precise treatment of your condition, it may take the privacy and security concerns from your smart watch, a mere wearable, and literally implant them into your heart. Who is liable if your heart is hacked and damage results? Does available insurance adequately cover the risks? Can patients be expected to understand enough about how the device functions to fully comprehend the scope of potential downstream risk? This panel will explore these and other issues at the frontier of Artificial Intelligence (“AI”) in healthcare.

The panelists will ground the discussion by first providing foundational details regarding the technical aspects of AI. When we refer to AI, what do we mean specifically? Which types of AI are most commonly used in healthcare applications? How do the features of those AI techniques affect analysis of legal issues in medical AI? How do non-technical lawyers get up to speed sufficiently to adequately perform the required analysis? This program will offer a short, introductory explanation of the technical fundamentals of AI that transactional lawyers should understand in order to effectively counsel clients building products and services at the intersection of AI and healthcare.

The program will then discuss some of the use cases of medical AI. Surgeons using smart scalpels. Dermatologists using AI-assisted research and data mining tools to assist with difficult diagnosis. Radiologists using deep learning algorithms to read diagnostic imagery with greater preciseness than human capability. Precision AI to detect breast cancer, as well as applications in cardiology, pathology and ophthalmology. The program will also touch on the ever-increasing availability of wearable and implantable medical AI. All of these use cases offer potential benefits of greater patient well-being through earlier detection and more effective treatment of disease. But with all technology, the benefits come with trade-offs.