The causes and countermeasures of artificial intelligence algorithmic bias and health inequity

Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2023-01-30 Cooperative journals: 《中国全科医学》

CHEN Long ZENG Kai LI Sha TAO Lu LIANG Wei WANG Haocen YANG Rumei

Abstract：

With the development of information technology, artificial intelligence shows great potentials for clinical diagnosis and treatment. Nevertheless, algorithmic bias in artificial intelligence can lead to problems such as unequal distribution of healthcare resources, which significantly affect patients’ health equity. Algorithmic bias is a technical manifestation of human bias, which is related to the process of artificial intelligence development, including data collection, model training and optimization as well as output application. Since healthcare providers have a direct impact on patients’ health, they should take measures to prevent algorithmic bias and related health equity. It is also important for healthcare providers to ensure the unbiasedness of health data, optimize the fairness of artificial intelligence, and enhance the transparency of its output application. In addition, healthcare providers also need to consider how to solve algorithmic bias and bias related health inequity in clinical practice in order to fully and properly protect patients' health equity. This paper reviews the causes and countermeasures of algorithmic bias in the health field to improve healthcare providers’ awareness and ability in identifying and addressing algorithmic bias, as well as provide empirical foundations for ensuring the health equity in the information age.

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