Artificial Intelligence (AI) shows the potential future of the health care industry. Understanding the factors that influence potential patients’ trust in incorporating AI into medicine will encourage not only health care providers, but also software development companies to invest in AI in medicine for better patient care as part of their business strategies. The goal of the current study is to gather feedback from individuals who reside in the United States or Thailand in order to gauge their level of confidence in AI in medicine. This descriptive study included 400 online survey responses. Half of the respondents live in the United States, while the other half live in Thailand. This study discovers that the quality (accuracy) of AI in medicine is the most important to the vast majority of participants (80.8%). Participants’ trust in AI in medicine grows as its quality (accuracy) improves. The majority of participants (67.1%) would likely trust AI in diagnosis and treatment if it were the only option available to them. The cost of AI is the least important factor in convincing the majority of participants (48%) to trust AI in medicine. The vast majority of participants (81%) thought AI doctor fees should be lower than traditional doctor fees. Nearly half of participants (47%) indicated that 90% to 100% accuracy is the accuracy level at which they would put their medical decisions in the hands of AI. The majority of participants (67.8%) would most likely use AI doctors for nonemergency situations for free in exchange for their health care data. There was a statistically significant difference between groups (the United States vs. Thailand) as determined by one-way ANOVA. Both groups show a positive attitude toward AI in medicine. The current study's findings may encourage AI technology providers to create affordable AI technology for health care providers in the near future.
Show LessHarnkham, N., Cassard, A., Au, A. & Shenosky, B. (2024). Trust in Artificial Intelligence for Patient Care: A Quantitative Descriptive Study [version 1] [preprint]. Computer Science.
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