A Guide to AI Challenges and Barriers
DOI:
https://doi.org/10.65539/31cay902Keywords:
artificial intelligence, social challenges, technology, medical bias, insuranceAbstract
Artificial intelligence (AI) tools are developing quickly and prominently within the U.S. healthcare system. It therefore seems essential to understand their weaknesses to practice medicine that is fully informed. The goal of this paper is to overview several key concerns surrounding healthcare AI, as well as some anticipated barriers to its implementation. AI’s generalizability is currently limited due to a widely fragmented Electronic Health Record (EHR) and inaccessibility to training data. AI tools are therefore at risk of acting on incomprehensive knowledge and generating inaccurate outputs. They are also extremely susceptible to several different forms of bias. Such bias can result in preferences towards diagnosing some diseases over others and recommending interventions that are only beneficial to certain populations. Privacy and transparency are also of great concern, especially when dealing with private medical data. While “black box” algorithms are criticized for their lack of transparency, innovators are working towards explainable AI (XAI) tools that can “show their work.” Developing guidelines make it difficult to predict how liability for AI malpractice may be distributed across parties but has interesting implications for how physicians will change their practice in response. Finally, the current U.S. payment structure does not easily accommodate healthcare AI tools. This challenge raises questions surrounding healthcare AI’s reimbursement mechanism as it becomes more widely utilized. While this paper does not provide solutions for the outlined concerns, it emphasizes the importance of understanding and anticipating the shortcomings of new healthcare technologies.
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Copyright (c) 2025 Rosemarie Burynski, Bernice L. Hausman (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
