In a recent interview about President Biden’s recent executive order on artificial intelligence (AI), Morris Panner, the president of Intelerad Medical Systems, shared his concerns that the executive order, while well-intentioned, may wind up stifling innovation and the continued evolution of AI in radiology.
While President Biden’s recently issued executive order on artificial intelligence (AI) emphasizes new standards for the development and use of AI models, Morris Panner has a few reservations and suggests that the executive order may turn out to be “HIPAA for AI” in some respects.
“As well intentioned as HIPAA (Health Insurance Portability and Accountability Act) was, it really shut off a generation of innovation in health care because of what it did to information flow and risk taking in innovation around data,” claimed Panner, the president of Intelerad Medical Systems, in a recent interview.
“I understand why we have HIPAA. We respect HIPAA. We care a lot about patient privacy. But HIPAA was and has continued to be something that most people don’t think really has lived up to its reputation as a portability act. In many ways, the executive order takes some legitimate problems and tries to address them but ends up doing it in a way that will stifle innovation and make it harder for us to take risks at the beginning of the AI innovation cycle.”
(For related content, see “How Will President Biden’s New Executive Order on AI Impact Radiology?,” “Can AI Improve Triage Efficiency in Radiology Workflows for Follow-Up X-Rays?” and “FDA Clears Emerging AI-Enabled Teleradiology Platform.”)
While the executive order references the bolstering of access to technical resources and assistance for smaller companies seeking to develop AI models, Panner suggests the executive order may lead to “a lot of registration and government examination” that would thwart smaller innovative companies and favor more established companies with larger regulatory capabilities but who are also more risk adverse.
For more insights from Morris Panner, watch the video below.
New Study Examines Short-Term Consistency of Large Language Models in Radiology
November 22nd 2024While GPT-4 demonstrated higher overall accuracy than other large language models in answering ACR Diagnostic in Training Exam multiple-choice questions, researchers noted an eight percent decrease in GPT-4’s accuracy rate from the first month to the third month of the study.
FDA Clears AI-Powered Ultrasound Software for Cardiac Amyloidosis Detection
November 20th 2024The AI-enabled EchoGo® Amyloidosis software for echocardiography has reportedly demonstrated an 84.5 percent sensitivity rate for diagnosing cardiac amyloidosis in heart failure patients 65 years of age and older.
FDA Clears Updated AI Platform for Digital Breast Tomosynthesis
November 12th 2024Employing advanced deep learning convolutional neural networks, ProFound Detection Version 4.0 reportedly offers a 50 percent improvement in detecting cancer in dense breasts in comparison to the previous version of the software.