Automated Inequality

The inequality discussed in this piece is like that in “Weapons of Math Destruction”, which make unsystematic categories to fit people in. This reading points out a very important danger of using data and algorithm as a tool to solve social issues: the algorithm, or the technology dominates the whole process and human beings have to fit the technology. Shouldn’t it be the other way around? With the high failure rate of technology in solving social problems mentioned in the article, how is it possible that people still believe in technology as a “neutral” and “objective” tool that can reduce human errors? The “automated” inequality and “quantified” “weapons of math destruction” have revealed the flaws of using data. When you need to deal with large amount of people, you kind of have to reduce them to a certain extent and sacrifice some of the individualism, which is important in solving such problems. As is mentioned in the infrastructure article, system thinking or relationality is important in studying media infrastructure. It is also important in studying human beings, who are themselves unique related systems rather than the aggregation of a bunch of segregated and meaningless categories. The organic systems of human beings are cut into unrelated pieces which people who interpret the data look for “correlations” that are may or may not mean anything in solving the problems. In addition, a lot of the readings on data speak about the dangers and flaws of data and algorithms, and they point out that data has dominated human beings’ lives instead of assisting them. But how do we solve the problems? How to implement data and algorithms to assist people to address the various social issues we are facing today since it is unlikely that we are going to drive data out of our lives because it is prevalent. How to make it a useful tool rather than coding biases into it and using algorithms to sabotage marginalized people and sacrifice their most urgent needs in favor of those of the richer middle class? Using data for real “public good” is a complex problem requiring various aspects of efforts from different disciplines and social organizations.