9/5/2019 7:53:00 AM Artificial intelligence in medicine raises legal, ethical concerns
Sharona Hoffman Case Western Reserve University
(THE CONVERSATION) The use of artificial intelligence in medicine is generating great excitement and hope for treatment advances.
AI generally refers to computers’ ability to mimic human intelligence and to learn. For example, by using machine learning, scientists are working to develop algorithms that will help them make decisions about cancer treatment. They hope that computers will be able to analyze radiological images and discern which cancerous tumors will respond well to chemotherapy and which will not.
But AI in medicine also raises significant legal and ethical challenges. Several of these are concerns about privacy, discrimination, psychological harm and the physician-patient relationship. In a forthcoming article, I argue that policymakers should establish a number of safeguards around AI, much as they did when genetic testing became commonplace.
Potential for discrimination
AI involves the analysis of very large amounts of data to discern patterns, which are then used to predict the likelihood of future occurrences. In medicine, the data sets can come from electronic health records and health insurance claims but also from several surprising sources. AI can draw upon purchasing records, income data, criminal records and even social media for information about an individual’s health.
Researchers are already using AI to predict a multitude of medical conditions. These include heart disease, stroke, diabetes, cognitive decline, future opioid abuse and even suicide. As one example, Facebook employs an algorithm that makes suicide predictions based on posts with phrases such as “Are you okay?” paired with “Goodbye” and “Please don’t do this.”
This predictive capability of AI raises significant ethical concerns in health care. If AI generates predictions about your health, I believe that information could one day be included in your electronic health records.
Anyone with access to your health records could then see predictions about cognitive decline or opioid abuse. Patients’ medical records are seen by dozens or even hundreds of clinicians and administrators in the course of medical treatment. Additionally, patients themselves often authorize others to access their records: for example, when they apply for employment or life insurance.
Data broker industry giants such as LexisNexis and Acxiom are also mining personal data and engaging in AI activities. They could then sell medical predictions to any interested third parties, including marketers, employers, lenders, life insurers and others. Because these businesses are not health care providers or insurers, the HIPAA Privacy Rule does not apply to them. Therefore, they do not have to ask patients for permission to obtain their information and can freely disclose it.
Such disclosures can lead to discrimination. Employers, for instance, are interested in workers who will be healthy and productive, with few absences and low medical costs. If they believe certain applicants will develop diseases in the future, they will likely reject them. Lenders, landlords, life insurers and others might likewise make adverse decisions about individuals based on AI predictions.
When it comes to genetic testing, patients are advised to seek genetic counseling so that they can thoughtfully decide whether to be tested and better understand test results. By contrast, we do not have AI counselors who provide similar services to patients.
The prospect of AI can over-awe people. Yet, to ensure that AI truly promotes patient welfare, physicians, researchers and policymakers must recognize its risks and proceed with caution.
This article is republished from The Conversation under a Creative Commons license.