Association for Public Policy Analysis & Management

The study of health risks intersects the boundary between Science and Technology Studies (STS) and public health policy. With the surge of breakthrough inventions and innovations driving the Fourth Industrial Revolution, new and emerging technologies present both opportunities and challenges to those dealing with issues related to health risks. In particular, big data and artificial intelligence technology in the medical field opens various paths for decisions, while requiring integrated insight from those making the decisions, and imposes a greater burden in terms of scrutiny.

Exploring the feature of a ‘risk society’ in reflexive modernity, sociologist Ulrich Beck has said “there is no expert on risk”. However, the imperfect and uncertain characteristics of risks has generated an increasing number of experts and massive data sets on particular risk subjects. In this era of abundant sources of knowledge, data quality and reliability becomes a critical aspect that must be considered to create the right policy and to be a guideline for a ‘better’ decision. The proliferation of a broad range of experts, massive data sets, and advanced computer technologies call for more negotiation, examination, and standards in order to arrive at an agreeable and reliable decision.

This study explores the strategies, tools and mechanisms for generating a standards model for brain health, particularly for stroke risk assessment in the context of building a national reference data system in Korea. The process in which large amounts of health information of individuals are encoded as ‘data’ to create a standardized model for determining the health of the brain will be examined. In particular, this research traces the development of statistical maps for diagnosing the brain disease White Matter Hyperintensities (WMHs), to illustrate how the concept of ‘certified risk’ is generated and put to use in the Korean society. This case study of statistical brain anatomical maps shows an interesting assemblage of health risk practices encompassing measurement science, computer technology, probability statistics based on big data, and standard-making procedures. This paper aims to shed light on contemporary risk governing practices by analyzing interactions of various actors, such as researchers, policy makers and clinical practitioners who are trying to gain a certain level of objectivity, accuracy, and reliability in governing public health risks within the framework of making standards. Lastly, this paper suggests important policy implications, arising from the imperfect elements medicine that bears multiple levels of ‘uncertainty’ and the language of standards, should be commonly understood and shared among medical professionals, patients, researchers, and most importantly policy makers who set rules, regulations, and guidelines.