Beyond Sanctions: The Malpractice Dimension of AI Hallucinations # Court sanctions for AI-generated fake citations have dominated headlines since Mata v. Avianca. But sanctions are only the visible tip of a much larger iceberg. The deeper exposure lies in professional malpractice liability, claims by clients whose cases were harmed by AI-generated errors that their attorneys failed to catch.
AI in the Emergency Department: Time-Critical Decisions # Emergency medicine is where AI meets life-or-death decisions in real time. From sepsis prediction algorithms to triage decision support, AI promises to help emergency physicians identify critically ill patients faster and allocate resources more effectively. In April 2024, the FDA authorized the first AI diagnostic tool for sepsis, a condition that kills over 350,000 Americans annually.
The Unregulated AI Therapist Crisis # Mental health AI exists in a regulatory vacuum. While the FDA has authorized over 1,200 AI-enabled medical devices, none have been approved for mental health uses. Meanwhile, millions of users, many of them vulnerable teenagers, interact daily with “AI therapists” and companion chatbots that their makers never intended to provide therapy but that users treat as mental health support.
AI Enters the Skin Cancer Screening Revolution # Skin cancer is the most common cancer in the United States, yet approximately 25% of cases are misdiagnosed. In January 2024, the FDA authorized DermaSensor, the first AI-enabled dermatologic device cleared for use by non-specialists, opening a new frontier for skin cancer detection in primary care settings.
AI Transforms Cancer Care # Artificial intelligence is reshaping every phase of cancer care, from early detection through treatment planning and survivorship monitoring. AI tools now analyze mammograms for breast cancer, pathology slides for prostate cancer, and imaging studies across multiple cancer types. But as AI becomes embedded in oncology workflows, critical liability questions emerge: When AI-assisted diagnosis misses cancer or delays treatment, who bears responsibility? When AI recommends treatment and outcomes are poor, what standard of care applies?
AI Transforms the Pathology Laboratory # Pathology, the cornerstone of cancer diagnosis, is undergoing a digital revolution. Whole slide imaging has transformed glass slides into gigapixel digital files, and AI algorithms now assist pathologists in detecting cancers, grading tumors, and identifying features invisible to the human eye. Paige AI’s 2021 FDA authorization marked the first-ever approval for AI in pathology, and the field has expanded rapidly since.
AI Revolutionizes Eye Disease Detection # Ophthalmology became the proving ground for autonomous AI in medicine when the FDA cleared the first-ever fully autonomous AI diagnostic system:IDx-DR (now LumineticsCore), in 2018. Today, AI systems can diagnose diabetic retinopathy at the point of care without a specialist, detect early signs of glaucoma and age-related macular degeneration (AMD), and guide treatment decisions. But with autonomy comes unprecedented liability questions: When AI screens for diabetic retinopathy in a primary care office and misses disease, who bears responsibility?
AI Transforms Cardiovascular Care # Cardiology has become a major frontier for artificial intelligence in medicine. From AI algorithms that detect arrhythmias on ECGs to predictive models forecasting heart failure readmission, these systems are reshaping how cardiovascular disease is diagnosed, monitored, and managed. But with transformation comes liability questions: When an AI misses atrial fibrillation and the patient suffers a stroke, who is responsible?
The Robotic Surgery Revolution # Surgical robotics has transformed operating rooms worldwide. The da Vinci Surgical System alone has been used in over 12 million procedures. Orthopedic robots like Mako assist in joint replacements with sub-millimeter precision. Yet with this technological revolution comes a complex liability landscape: who is responsible when a $2 million robot malfunctions, when a surgeon lacks adequate training, or when a hospital fails to maintain the equipment?
The Frontline of Medical AI # Radiology is where artificial intelligence meets clinical medicine at scale. With over 870 FDA-cleared AI algorithms, representing 78% of all medical AI approvals, radiology is both the proving ground and the liability frontier for AI in healthcare. When these algorithms miss cancers, misidentify strokes, or generate false positives that lead to unnecessary interventions, radiologists and healthcare systems face mounting legal exposure.
Liability Allocation # Who is liable when AI makes a mistake, the user, deployer, or vendor? # The short answer: it depends on the circumstances, but deployers typically bear primary responsibility.
Healthcare represents the highest-stakes arena for AI standard of care questions. When diagnostic AI systems, clinical decision support tools, and treatment recommendation algorithms are wrong, patients die. With over 1,250 FDA-authorized AI medical devices and AI-related malpractice claims rising 14% since 2022, understanding the evolving standard of care is critical for patients, providers, and institutions.