Data Science, Politics, and the Society

The emerging field of data science, which involves extracting and using information from large amounts of unstructured data (Wikipedia), falls into the realm of ‘politicized’ science. The large amounts of data that are used for analysis include user generated data from social media, e-mails, videos, blogs, activity tracking from websites – to name a few. Apparently, with the domain expertise and statistics, experts and hackers tend to use a lot of user generated data without proper consent which has ignited a lot of debates and controversies in the society and made its way into the political sphere. Online e-commerce websites, for instance, are tracking users’ clicks and activities to improvise their service and drive more traffic. On the other end, politicians are making use of big data to their advantage in political campaigns. For instance, Obama and his team used big data analytics to drive the 2012 presidential election and get people to vote. Hence, directly or indirectly, data science is intersecting with the political sphere and is becoming a debatable subject or rather a more political issue (Scheufele).

Data science plays a role in several social contexts. As increasing organizations start to implement Big Data, the global economy is most likely to be affected which in turn will affect the society. According to McKinsey report, innovation in data science and Big Data can potentially add $ 300 billion value per annum to US health care, and an increase in consumer surplus by $600 billion (datafloq.com). These advancements are likely to boost the economy and improve consumer sales. The negative side to these developments is the breach of privacy of consumers. Consumers will always feel like someone is watching and tracking them while they shop online or update on social media. Twitter, for instance, sold a tweet archive to a broker; Path – a photo sharing and messaging service – confessed that they used user data without permission. The misuse of Big Data is inevitable and people are in favor of rigid legislations and regulations in that sector. Another sphere where big data plays an important role is in global biomedical research where researchers, funders, and health care providers are asking for a global alliance in order to share big data related to genomics in order to enhance clinical care and address global issues pertaining to the field. Hence, ranging from business to health care, data science is seeing growth in several social contexts.

It is critical to assess the reasons behind why data science has become ‘politicized’. This is related to the four aspects of modern science as portrayed in the course material (Module B). Data science adheres to these four aspects. Firstly, with increasing research and development in the field, data scientists are formulating complex ways to handle and process Big Data for numerous useful applications. On the other hand, as the field grows, various resources and softwares such as Apache Spark and data processing engines, make the work of data scientists easier and simpler. Secondly, data science makes use of theories and information from several fields including mathematics, nanotechnology, robotics, computer programming, information technology and theory, machine learning, etc. Data science applies knowledge from these disciplines as well as affects research in sectors including health care, business, bioinformatics etc. This is where data science comes in intersection with these disciplines. Thirdly, like all modern sciences, data science has seen faster bench to bedside transitions in form of direct applications of the processed big data which can drive important conclusions about real world problems. Google, for example, is using Instagram food posts to count calories using its complex algorithm and big data expertise. In other words, with existing resources, the Big Data is already there, and the increasing expertise in processing this data and to carve it the way one wants leads faster transition to real world application. Finally, data science ties itself to various ethical, social and legal implications. The breach of privacy while accessing user data is a major one. The positive implications include improved user experience and an outgrowth of several applications that can create a positive impact on some of the global issues.