How Big Data is Defining Human Value
In chapter 8 of “Weapons of Math Destruction (WMD),” by Cathy O’Neil, she addresses how mathematical model are incorporated in banking and finance, and how it is causing harm to our society. She points out how credit scores are evaluated through e-scores, which an unregulated and unfair mathematical model does. E-scores consist of various data such as zip codes and internet activities as input to the model. Financial institutes use E-scores to form a hierarchy of potential customers who visit their website, such as the case for Capital One.
The e-score evaluator is opaque and lacks transparency because most individuals are often unaware that their e-score is evaluated when they visit banking websites. People living in poor areas are often targeted by the model and are given low credit scores, making life more difficult for those who are already struggling. Thus, those who are in poverty have little chance and difficulty of escaping poverty. It also widens the wealth inequality in society. On top of that, not only are people living in poor areas are being targeted, but also individuals who share the same name as criminals. Online databases are incorrectly labeling people as dangerous individuals. While it is a mistake, most people rely on technology for accuracy. Thus, these mistakes can affect a person for the rest of their life.
In the topic of ethics, O’Neil mentions that most data scientist is aware that race is not a valid input for a model, but they fail to recognize that zip codes are also invalid inputs. Credit scores are not only being used to determine whether a person receives a loan or not. They are also being used to determine whether a person is “good” in many different aspects such as dating sites, applying for jobs, and job promotions. Therefore, the e-score model also has the WMD characteristic of scalability in the financial sector and other different sectors. However, not all hope is lost. Some states have already taken steps to ban the use of credit scores in the hiring process.
