Calvin Ho et al on Trustworthy Use of AI & Big Data Analytics in Health Insurance (WHO Bulletin)

"Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance"

Calvin W L Ho, Joseph Alib & Karel Caalsc
Bulletin of the World Health Organization
Volume 98, Number 4, pp. 229-296

Published in April 2020

Abstract: Technological advances in big data (large amounts of highly varied data from many different sources that may be processed rapidly), data sciences and artificial intelligence can improve health-system functions and promote personalized care and public good. However, these technologies will not replace the fundamental components of the health system, such as ethical leadership and governance, or avoid the need for a robust ethical and regulatory environment. In this paper, we discuss what a robust ethical and regulatory environment might look like for big data analytics in health insurance, and describe examples of safeguards and participatory mechanisms that should be established. First, a clear and effective data governance framework is critical. Legal standards need to be enacted and insurers should be encouraged and given incentives to adopt a human-centred approach in the design and use of big data analytics and artificial intelligence. Second, a clear and accountable process is necessary to explain what information can be used and how it can be used. Third, people whose data may be used should be empowered through their active involvement in determining how their personal data may be managed and governed. Fourth, insurers and governance bodies, including regulators and policy-makers, need to work together to ensure that the big data analytics based on artificial intelligence that are developed are transparent and accurate. Unless an enabling ethical environment is in place, the use of such analytics will likely contribute to the proliferation of unconnected data systems, worsen existing inequalities, and erode trustworthiness and trust.  Click here to read the full article.

摘要: 确保人工智能和大数据分析在医疗保险中的可靠使用 大数据（即，可以快速处理大量不同来源的高度差异 化数据）、数据科学和人工智能领域的技术进步可以 改善医疗系统功能，促进个性化护理和公益服务。然 而，这些技术不会取代医疗系统中的道德领导和治理 等基本组成要素，也不会消除对稳健的道德和监管环 境的需求。在本文中，我们讨论了医疗保险大数据分 析中的稳健道德和监管环境可能是什么样子的，并且 举例描述了应该建立的保障和参与机制。首先，一个 清晰有效的数据治理框架至关重要。需要制定法律标 准，并且鼓励和激励保险公司在设计和使用大数据分析和人工智能方面秉承以人为本的理念。第二，必须 有一个明确的问责流程来解释可以使用哪些信息以及 如何使用这些信息。第三，对于数据被采用的人员， 应该通过积极参与决定如何管理和治理其个人数据的 方式为其赋权。第四，保险公司和治理机构，包括监 管机构和政策制定者，需携手合作，确保基于人工智 能开发的大数据分析是透明且准确的。除非具备有利 的道德环境，否则使用此类分析很可能会导致未连接 的数据系统的分散，加剧现有的不均衡情况，并降低 可靠性和可信度。