管理(神学)
医学
义务
人工智能
人工智能应用
机器学习
数据科学
风险分析(工程)
计算机科学
政治学
政治
法学
作者
David A. Gudis,Edward D. McCoul,Michael J. Marino,Zara M. Patel
摘要
Artificial intelligence (AI) is ubiquitous and expanding, and the healthcare industry has rapidly adopted AI and machine learning for numerous applications. It is essential to understand that AI is not immune to the biases that impact our clinical and academic work, and in fact may inadvertently amplify rather than reduce them. As we harness the power of AI, it is our obligation to our patients to ensure that we address these concerns. We must take responsibility for proactive stewardship to protect against bias, not only for new AI algorithms, but also for our research studies that may one day provide data for those algorithms.
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