ETEC 511 – IP #3: Algorithms

Option I: Content Prioritization

“At a time when state funding for public goods such as universities, schools, libraries, archives, and other important memory institutions is in decline in the US, private corporations are providing products, services and financing on their behalf. With these trade-offs comes an exercising of greater control over the information, which is deeply consequential for those already systematically oppressed…” (Noble, p. 123)

Think and respond to the following questions:

  • Explain in your own words what “content prioritization” (Noble, p. 156) means (give some examples) and how (in lay terms) content prioritization algorithms work. With control over the “largest digital repository in the world” (Noble, p. 187), how have Google’s content prioritization algorithms been “consequential for those already systematically oppressed”? How do they impact your professional life? (give specific examples and briefly discuss)
  • What are some ways PageRank impacts your personal life? (specific examples and briefly discuss) (How) can you impact PageRank? Explain.

Content prioritization essentially is a resorting algorithm based on a myriad of factors. In Google Search, it is based on things like location data, prior search history, demographic information about your account, and other personalization. While this might seem like a good and useful thing, it does often lead one down a rabbit hole. Google Search, like most sites, wants your attention. The more time you spend with it the better. The more searches, means that they can build a better profile of you and what you want to see. I will come back to that in a moment.

When people started figuring out how to improve their own sites search ranking, they started to manipulate link text to manipulate Google’s algorithm for search ranking. This lead to using potential misleading link text (the early internet history’s version of being Rick-Rolled) to mislead users through a process called Google Bombing. As these became passed around early social media, they also caused Google to rank them higher in priority based on the number of searches being run for the search term. The one that might be memorable was during the second Iraq War, anti-war groups made an effort to link “miserable failure” to the White House’s website. Typically, these Google Bombs were not long-lasting, as you can see from Google Search trends for the phrase “miserable failure”. However, their impact was.

The manipulation of search ranking was seen as a strategy from radical right groups (McSwiney in Devries, Bessant & Watts, 2021, p. 25) to access, recruit and radicalize users. The sheer volume of racist propaganda online is almost pervasive. If one of Google’s search algorithm key ranking criteria is based on volume of links, it is no wonder that racist, biased sites get pushed up the rankings. One of Noble’s arguments throughout the book is that while Google builds the algorithm that pushes certain sites to the top of the pile, they are not responsible for it (Noble, 2018). So, it follows when Google autocompletes a search query with a stereotypical response, that has an impact on the viewer – either reinforcing a negative view or potentially introducing self-doubt and the ranking algorithm every time it is clicked.

In my professional work, I often am searching websites for documentation about educational technology products. I am often working on a work account which has little to no demographic information, never search logged in, with no location technology able to be queried. Essentially, my work account is a bit like a burner account. So typically, no, I do not see any evidence of discrimination, however documentation does have discrimination built into it – the types of archetypes used, the images of people describe more about the company than many think. However, from a search perspective, I do not use Google autocomplete ever, I do not use Google as a sole search provider, I move around (Duck Duck Go and Bing are two suitable competitors), so that there isn’t much to give to one provider.

Back to the popularity contest that is PageRank, and attention. While I do not use Google exclusively, PageRank’s algorithm strategy is pretty pervasive amongst search. It is part of what was taught at Udacity’s big “build a search engine” MOOC (I completed this in 2012?) and is what Yandex and Bing use to scrape the web for links, and to count the number of links that point to a site with a set of keywords. It is a common strategy and would like yield common results – except you do not have the ranking algorithm component, but both ranking and link scraping work hand in hand. The first way that PageRank influences daily life is the reliance on what is popular over what is factual. I have seen this over and over, popular misconceptions – and how tales take over the reality of what happened. Sure, we have context for some of that (in that disadvantaged groups often do not get their stories told at all) but Google’s focus on popularity assumed (when PageRank was developed initially) that people are mostly truthful. Instead, 15 years later, it is less about people and more about how many resources can be deployed to increase site ranking, essentially privileging the wealthy (who are disproportionally white, heterosexual and male) and resourceful.

Well, one way to circumvent PageRank is to Google Bomb it to uselessness. Essentially fill it with obfuscated information. However, that only punishes you – because it makes it less useful to you. One other way to make PageRank be influential is to pay less attention to it and SIFT the sources. Go straight to the source rather than Google Search everything (the number of times I have seen someone search for the website, rather than just type the site address is more than I can count in the last decade). Use other search engines. Avoid giving attention to things that are false. Support platforms that do not combine personal data with search results.

References

Devries, M., Bessant, J., & Watts, R. (Eds.). (2021). Rise of the far right : Technologies of recruitment and mobilization. Rowman & Littlefield Publishers.

Noble, S. (2018). Algorithms of Oppression : How Search Engines Reinforce Racism. NYU Press.