ABSTRACT
In this chapter, I elucidate the significance of big data for the philosophy of public health. I do so by describing key big data methods used in public health and by examining several conceptual and ethical issues raised by these methods that are of particular philosophical concern. After characterizing the big data approach, I survey four issues. First, I discuss contrasting views about the roles of theories and values in data-driven research. Then, I consider how the implementation of big data techniques bears on privacy. Next, I clarify the criticism that some of these techniques are inscrutable and thus offer little explanatory insight. Finally, I explore the contention that the use of big data methods exacerbates health disparities. Throughout, to illuminate each of these issues, I review recent examples of big data in public health. In so doing, I explain relevant features of big data techniques, such as the construction of massive data sets from heterogenous sources and the use of deep-learning algorithms to make predictions. I conclude by highlighting how each of the conceptual and ethical issues that I detail in this chapter pertains to the field of omics research.
