The intersection of technology and healthcare has reached an unprecedented point in history. The traditional medical model, where the ability to accurately diagnose and treat patients is gained from thousands of hours of hands-on medical training, is being challenged. The challenge comes from the creation of artificial intelligence (AI) software that can use deep learning to meet or exceed the accuracy and dependability of medical decisions made by their human counterparts. These AI systems function as an “economy of minds” using collective experiences of human physicians and healthcare providers to create massive databases of knowledge that can be trained to perform specific undertakings. AI already infiltrates fields such as radiology, optometry, and some simple surgeries. But what happens when the initial programming has been outgrown by the learning of the technology and the technology makes a mistake. Who becomes the tortfeasor? The doctor relying on the AI? The hospital paying for the AI? Is the company responsible for the initial programming? Or is no one liable?
This paper will challenge the current application of the technology’s ethical considerations facing a healthcare provider using AI and explore the use of AI systems in medical decision making. I will divide my argument into five parts. Part I will define AI by deciphering a very complex, technical topic understandable language. Part II will break down AI into the three primary classifications of AI systems that will be important to delineate as these types of systems are discussed. Part III will explore the current and potential uses of AI in healthcare by giving more concrete examples of AI applications when mass amounts of data are available. Part IV will identify significant concerns with the ethics of AI as we know it today but specifically, focus on the reliability concerns of a healthcare provider using an AI system for diagnosis or treatment planning. We will also look at how current law intersects with innovative AI. Finally, in Part V, I make a recommendation considering the use of AI in healthcare and how the symbiosis of such tools can be maximized while at the same time limiting risk.
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