Data’s Traces of Bias Against Minorities

Introduction to The Display Of Bias With Minorities

Our readings this week show the ways big data is able to display bias against minorities. The idea of bias towards minorities has been etched into the American culture since the start. Multiple ways the week showed the ways big data is able to display bias against minorities. The readings this week focus on Nextdoor an app used for people within neighborhoods to connect with each other, and how healthcare has changed the way it cares for its patients. Both have a way of excluding groups of color especially, but also minority groups as well as they see unfavorable. These broken algorithms only lead for digital ways to show blatant separation for different groups in America.

Traces of Bias in Healthcare with Minorites

Healthcare providers offer services to everyone in their communities. It is sad to know that giving service could depend on who you are in society, and not just rendering help to those in need. This is something that has been happening over time. The article Assessing Risk, Automating Racism by Ruha Benjamin mentions both the Tuskegee Study as well as the Henrietta Lacks story. Both very controversial moments for people of color. Both show times healthcare are able to take advantage of those with lesser and even give them less help than others. This goes against the medical oath care providers take. Healthcare jobs require empathy. The algorithms lacks empathy. It is instead showing them who can pay for their services. This is good for numbers, but bad for the people who trly need services.

Redlining and Traces of Bias With Minorites

Housing communities are no different than the healthcare communities as it comes to exclusivity. They are selective of who they allow in, but this is all by design. The past still finds its ways into the practices for todays neighborhoods by way of apps. The article Digital Redlining The Nextdoor App and the Neighborhood of Make-Believe explores the Nextdoor App. This allowed homeowners and renters in neighborhoods were Abel to communicate. The information being put up started having certain post that went against community guidelines, but were still up to view. These were post about minorities possibly in the community that may look suspicious. Later when this was brought to the apps attention they tried to find a solution. Asking more questions from consumers posting on the app. This showed there interest in the consumer of their app, and wanted everyone within these communities to feel comfortable, unlike other times.

Big Data And Mistreatment

The misuse of the information being collected from consumers has been evident since the beginning of the semester. The readings so far have picked and poked to display ways big data proves to be rigged. Te consumers are not getting real results from the information being collected. This is hurting communities and I have brought this to light in other blogs from the semester. it seems that the system of algorithms put in place to help are hindering the growth and development of society when it comer to bias ways.