2 Dilemma

2.1 The Power (and Promises) of Data Science

Data science has contributed to breakthroughs in nearly every discipline, leading to some of the most striking advances and discoveries of the 21st century.

Some noteworthy contributions of data science include (Wamba et al., 2015):

  • Creating transparency
  • Enabling experimentation to discover needs
  • Exposing variability and improving performance
  • Segmenting populations to customize actions
  • Replacing/supporting human decision making with automated algorithms
  • Innovating new business models, products and services

Within our daily lives, the ability to parse large volumes of data to identify useful information is paramount. To name a few: web search engines optimized to return the most useful links, caller ID warning us not to pick up spam calls, recommender systems helping us find new music, real time traffic updates, speech to text, and instant language translation technologies. These mundane tasks belie revolutionary technological advances enabled by stores of big data that have also been used to elevate living standards and develop life-saving technologies.

2.2 The Problem of Data Science

The application of data science has drastically affected cultures and social structures on a rapid scale, sometimes with unintended consequences. For example, web search engines optimized to return the most useful links are built to prioritize popularity without taking veracity into account, which can contribute to the spread of misinformation. Caller ID can create a false sense of security because scammers have learned to make legitimate seeming names and numbers appear. Recommender systems helping us find new music could be limiting the socio-cultural diversity of the artists we listen to. Despite its accolades, data science is also blamed for perpetuating and exacerbating racial bias and harming disenfranchised populations.

2.3 Good or Evil?

So, which is it? Is data science the next stage in science’s evolution, necessary for advancing medical, environmental, biological and social science disciplines? Or is data science just a new way for those in power to control wealth, access to information, and influence the masses?

To approach this question, let’s start at the beginning and learn about the history of data science.