Content prioritization is a way to organize things. Humans prioritize all the time whatever we do. An ESL teacher prioritizes a course content at the beginning of the semester after studying students’ diagnostic test results, and then the educator does that every day with the material for studies, according to the students present in class and their particular needs. Applied to algorithms, content prioritization means records “presented in a ranking order” (Noble, 2018, p. 123).
Algorithms are a sequence of actions to do to solve a problem or complete a task. There are several types of them: randomised, recursive, backtracking, basic graph, greedy ones etc. (Erickson, 2019). Similar to a prioritization technique, algorithms are here to make our life more organized too, and they analyze massive amount of information for that. We have to remember though that these helpful and expensive algorithms act with “ruthless pragmatism” (Crawford, 2021, p. 95), for the benefit of someone else as well.
Exploring search engines as modern algorithms, Noble (2018) warns us that “search is a mirror of users’ beliefs” (p. 15) and in today’s flawed, prejudiced and unfair society search results are pampered too. She points out that “results are then normalized as believable and often presented as factual” (p. 25). O’Neil (2017) develops on that stating that “many poisonous assumptions are camouflaged by math and go largely untested and unquestioned” (p. 7) and calls algorithms “opinions embedded in mathematics” (p. 21). She believes that algorithms disadvantage poor people and minorities because algorithms, people who use them, and society in general are not perfect. In this regard, Noble (2018) particularly worries about Google’s “considerable control over personal identity” and what can circulate online or be forgotten (p. 123).
Indeed, modern algorithmic bias is so obvious sometimes it looks absurd. If one tries to google “best movie of … (any recent year)”, they will be surprised with the very diverse results from different online resources. Assuming that those numerous rankings were made to attract a potential watcher, contradicting outcomes actually have the opposite effect – they turn people away from those unreliable recommendations.
Still, despite everything turning into content (Taylor, 2021), and algorithms urging people to pay attention to this and that, it is a person who makes a final decision, a conscious choice. For instance, Facebook posts in my news feed nudge me toward certain political, economical or cultural views every day. Moreover, my humane acquaintances who support Ukraine, Russia, Europe, or independent republics in what is going on in Ukraine want me to back up their position exclusively. But since 2014 I have learned how to navigate those contradictory demands safely.
I think algorithms impact my professional life positively: I like how they assist me in finding any specific information – Google’s ranking algorithm PageRank being exceptionally good at that, and I appreciate their personalization efforts even though I do not share much about myself online. I am glad that Canadian children learn coding and programming in school. Of course, those computational skills – decomposition, pattern recognition, abstraction and algorithmic (i.e., logical) thinking – are nothing new for the psychologists. Still, it is good to know that mathematics is popular again.
That established Afro-American hairdresser from Noble’s (2018) negative algorithm example relied on Yelp too much for her business, in my opinion. She could have printed her own advertisements – with her photo and years of professional experience – and put them on every physical advertising site in her community. I am sure that owners of small businesses around would have gladly assisted her by positioning her messages near their entrances as a neighbour-to-neighbour favour.
If we accept that algorithms are valuable to us while they can also be for-profit, politicized and biased, it will make it easier to put up with their negative features and enjoy positive ones. Let us take YouTube’s business as an example. They play commercials with free videos and then suggest people should pay to avoid wasting time. Well, in these circumstances, my young yet already wise adult ESL students used to say, “Advertisement is an exercise in English listening too”, so we were not really bothered with those merchandising interruptions in class.
Or I get Canadian and world news from Yahoo.ca daily, mixed with barely hidden advertisements. If at first it felt unpleasant, currently I just skip any irrelevant information without thinking. I deal with other unwanted algorithmic recommendations pretty much the same way. I try not to impact PageRank or any other ranking systems by guarding my online presence. If I had a site I wanted to make more prominent though, I would write much on the topics that I am familiar with to create original and high quality content, would use keywords and hyperlinks, and make my pages internally linked for beginning.
Algorithms are a product of today’s world; they will be here with us for some time, and it is better for them, their creators and society to co-exist peacefully. Noble (2018) believes that search engines are “corralling and controlling the ever-growing sea of information” and to get accurate and neutral information one has to be more algorithmic literate (p. 25). It seems to me that sound scepticism and a bit of common-sense help see through any evil intentions too.
If we are cautious, use common sense and diversify, algorithms will stay friends.
References
Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press. https://doi.org/10.12987/9780300252392
Erickson, J. (2019). Algorithms. https://jeffe.cs.illinois.edu/teaching/algorithms/book/Algorithms-JeffE.pdf
Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press. https://doi.org/10.2307/j.ctt1pwt9w5
O’Neil, C. (2017). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group.
Taylor, A. (2021, February 2021). Are streaming algorithms really damaging film? BBC News. https://www.bbc.com/news/entertainment-arts-56085924