Prior to this module, I was familiar with how bias can be engrained within the archive, as discussed by Michel-Rolph Trouillot, but I honestly had never thought about how something as simple as a Google search could generate so much harm and this reality sickens me. While completing this module I had to repeatedly take breaks as I was so appalled and flabbergasted by how the Internet can be used to perpetuate hate. While I am on the Internet all the time via too much Instagram doom scrolling and unnecessary online shopping, my “personalized feed” as Dr. Noble described it, kept me ignorant of how bias is spread via search engines. All our readings for this module showcase how search engines contain bias and this reality is particularly frightening. Referred to as the great “equalizer,” technology is meant to democratize access to knowledge, yet as scholars and users of the Internet we must ask ourselves what knowledge/information is being disseminated and made most accessible (Dr. Noble’s Power, Privilege, & the Imperative to Act Talk).
I was really taken aback by the work of Dr. Noble and her talk, Power, Privilege, & the Imperative to Act, as she provided multiple examples of how search engines can be manipulated to perpetuate “algorithms of oppression” which in turn spread racism, sexism, white supremacy, and overall hate. I was particularly disgusted by how racist and hyper-sexualized stereotypes of women of color were the first results of a digital search engine used in Dr. Noble’s research. Additionally, Dr. Noble discussed how white supremacist and anti-Semitic groups have created harmful websites and bought space to allow these websites to show up as the first few results in search engines. Demeaning the legacy of Martin Luther King Jr. and supporting Holocaust denial, these websites spread hateful lies that are easily accessible via Internet search engines. Within the first few search results, search engines also produced racist references to the Obamas. The old saying “Don’t believe everything you see on the Internet” couldn’t be any truer than it is when encountering hateful websites. Dr. Noble characterized the harm of these search results perfectly, as the dissemination of these lies can lead to people actually believing them and threatening the well-being of minority groups (https://open.library.ubc.ca/cIRcle/collections/55474/items/1.0220808).
As Sharon Block shows us, even JSTOR (which I use all the time for school) has bias engrained within its vocabulary tag systems!! This really scares me, as the last thing I want to do is to misrepresent someone or have limited access to the media that accurately depicts the experiences of minority groups. JSTOR’s search system has been guilty of misrepresentation and glossing over topics discussing minority groups, placing unnecessary obstacles to work through when conducting this research (it’s just like the silencing Trouillot was talking about!!) Taking inspiration from Trouillot, I have approached my archival work with an understanding of how bias has “silenced” stories of minorities in the archive, but now I understand that I need to approach my scholarly Internet searches with even more caution (https://dhq.digitalhumanities.org/vol/14/1/000448/000448.html).
As S.L. Ziegler discusses, even the collection of data for online cultural resources can perpetuate misrepresentations of minority groups, causing a level of distress similar to that caused by the invasive marketing tactics of data brokers (https://dhq.digitalhumanities.org/vol/14/2/000462/000462.html).
There is a dark side to the digital world and our readings provide multiple examples of how digital tools have been manipulated to spread hate, yet how can we counteract the biases engrained in search engines? In the work titled after this concept, Algorithmic Accountability champions the idea that through “the assignment of responsibility for how an algorithm is created and its impact on society; if harm occurs, accountable systems include a mechanism for redress” that can counteract digital occurrences of bias (Caplan et al., 22). As Noble, Caplan (+ et al), Block, and Ziegler describe, we can stop the spread of hate via the Internet through awareness and by adopting a checking system of digital sources, like search engines, to counteract bias.