Our society has an inequality problem that spans across (arguably) every industry. Healthcare is towards the top of the list of industries affected by inequality not only because it perfectly demonstrates the issue, but because it is an essential part of human health and well being. In the United States, it is well accepted that racial minority groups receive lower quality healthcare than dominant groups. Not only do these groups feel discriminated against in healthcare settings, but they are also less likely to receive preventative care (Egede). However, as new technologies develop through the analysis of big data, the healthcare field is making huge strides towards expanding public health. As the capabilities of the healthcare industry increase, we would hope that the benefits of these new technologies would be shared with all people. But are these new technologies, used in healthcare and other sectors, really benefiting everyone equally?
One of the new technologies in healthcare that utilizes big data is called PRS, or Polygenic Risk Scores. These scores are used to predict the risks for people developing certain diseases and to suggest preventative measures accordingly. One study, published in Nature genetics, demonstrates that risk predictions from the PRS are far more accurate for people of European descent. The risk prediction of the PRS is most accurate when there is minimal genetic divergence between the person having their risk tested and the genetic data being used. According to the study, 79% of genetic data comes from people of European descent, when they represent only 16% of the global population. Because of this overrepresentation of European descendants in genetic research, the PRS risk predictions for people who are not of European descent are not very accurate and therefore not very useful.
Figure 1: This figure demonstrates the differences in predictive power of the PRS technology between different ancestry groups.
These PRS tests cost only about fifty USD per person and can be very helpful in educating people about preventative healthcare measures. However, they are useless to a majority of the global population if we don’t work to ensure that all racial and ethnic groups are well represented during the collection of genetic data used to map these types of predictions.
This study is demonstrative of an overarching problem that comes along with the use of big data. Although technology that utilizes Big Data has the potential to be beneficial to a global population, a lot of it, like the PRS, is only valuable to select groups. These technologies, if further developed in the same way, will only exacerbate the inequalities that already plague modern society, and healthcare is not the only field exploring the benefits of these new algorithms. Technology that utilizes big data is being developed for almost every industry. Healthcare is joined by marketing, science, law, retail,and many more. In each of these fields there is already inequality, and if new technology is continued to cater to one group of people, not only will they remain at the top of the social hierarchy, but the gaps of inequality will grow.
Like the inequality gaps between racial groups, the gaps between people with varying socioeconomic status can also be expanded through Big Data tech. One mechanism to explain this trend is that not all competitors have equal access to Big Data. The companies that are able to invest in developing Big Data technologies are those that are already at the top of their sector: Google, Amazon, American Express, and other massive corporations. These companies are already monopolizing their industries, and their access to Big Data analysis has the potential to cement their dominance even further. Companies can use this new tech to determine customer demand better than ever before, and their prediction abilities will only increase as new technology is developed. This trend allows them to outperform competitors who don’t have access to Big Data. Small and local business owners already struggle to compete, and through new tech they will be left behind while the bigger corporations continue to grow.
As demonstrated by examples in two diverse industries, healthcare and marketing, Big Data has the potential to further inequalities that are already a huge issue in society. If Big Data is to be used in a socially just way, we need to ensure that it is taken for all groups, and is accessible to more than just the top 1%. If we don’t promote equality when Big Data is on the table, privileged and majority groups will further dominate, leaving many classes of people behind.
References:
Egede, Leonard E. “Race, Ethnicity, Culture, and Disparities in Health Care.” Journal of General Internal Medicine. Blackwell Science Inc, June 2006. Web. 29 Mar. 2019.
Martin, Alicia R., Masahir Kanai, Yoichiro Kamatani, Yukinori Okada, Benjamin M. Neale, and Mark J. Daly. “Clinical Use of Current Polygenic Risk Scores May Exacerbate Health Disparities.” Sci-Hub. Nature Genetics, Apr. 2019. Web. 29 Mar. 2019
Data/Society/Decision-making Spring 2019 