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从新西兰制定新冠病毒算法治理框架中吸取的经验教训。

Lessons learned from developing a COVID-19 algorithm governance framework in Aotearoa New Zealand.

作者信息

Wilson Daniel, Tweedie Frith, Rumball-Smith Juliet, Ross Kevin, Kazemi Alex, Galvin Vince, Dobbie Gillian, Dare Tim, Brown Pieta, Blakey Judy

机构信息

School of Computer Science, Waipapa Taumata Rau/University of Auckland, Auckland, New Zealand.

Auror Ltd., Auckland, New Zealand.

出版信息

J R Soc N Z. 2022 Sep 19;53(1):82-94. doi: 10.1080/03036758.2022.2121290. eCollection 2023.

Abstract

Aotearoa New Zealand's response to the COVID-19 pandemic has included the use of algorithms that could aid decision making. Te Pokapū Hātepe o Aotearoa, the New Zealand Algorithm Hub, was established to evaluate and host COVID-19 related models and algorithms, and provide a central and secure infrastructure to support the country's pandemic response. A critical aspect of the Hub was the formation of an appropriate governance group to ensure that algorithms being deployed underwent cross-disciplinary scrutiny prior to being made available for quick and safe implementation. This framework necessarily canvassed a broad range of perspectives, including from data science, clinical, Māori, consumer, ethical, public health, privacy, legal and governmental perspectives. To our knowledge, this is the first implementation of national algorithm governance of this type, building upon broad local and global discussion of guidelines in recent years. This paper describes the experiences and lessons learned through this process from the perspective of governance group members, emphasising the role of robust governance processes in building a high-trust platform that enables rapid translation of algorithms from research to practice.

摘要

新西兰对新冠疫情的应对措施包括使用有助于决策的算法。新西兰算法中心(Te Pokapū Hātepe o Aotearoa)成立的目的是评估和托管与新冠疫情相关的模型和算法,并提供一个集中且安全的基础设施,以支持该国的疫情应对。该中心的一个关键方面是组建一个合适的治理小组,以确保所部署的算法在可供快速且安全实施之前接受跨学科审查。这一框架必然涵盖了广泛的观点,包括来自数据科学、临床、毛利人、消费者、伦理、公共卫生、隐私、法律和政府等方面的观点。据我们所知,这是此类国家算法治理的首次实施,它建立在近年来对相关指南进行的广泛本地和全球讨论的基础之上。本文从治理小组成员的角度描述了在此过程中获得的经验和教训,强调了稳健的治理流程在构建一个高信任平台方面的作用,该平台能够实现算法从研究到实践的快速转化。

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