Algorithms - Intellectual Productions - ETEC 511

In this intellectual production we're going to discuss how algorithms affect our lives and the influence they have in how we navigate the digital sphere. In particular we're going to discuss Google, who for many is the gateway to the web. For a company with this much power and influence it's important to understand how their policies, data collection and algorithms function within our lives.

To begin let's look at content prioritization. This is how algorithms decide what you see first. It's the process of ranking information, pushing what's deemed most relevant to the top of your search results, social media feed, or recommendation list. This isn't just about popularity; it's a complex calculation influenced by commercial interests, design choices, and deeply embedded societal biases. For example, Netflix may prioritize their own original content above content licensed from other studios to encourage more viewers to engage with it. Or content containing 2SLGBTQ+ commentary may be deprioritized in countries that don't recognize queer rights.

So how exactly does that work? First, the algorithm would index the web, creating a massive catalogue of trillions of pages. When you type in a query, it attempts to understand your intention to search that catalogue for any pages that match. From here it looks at hundreds of factors simultaneously in order to rank the results. Some factors it looks at are if the keywords appear on the page, how reliable the link is based on Google's PageRank algorithm, and the freshness of the content. Then based on results it assembles them for you on the results page.

As Safiya Noble (2018) explains, with control over the largest digital repository in the world, Google’s seemingly neutral algorithms can have severe consequences for already marginalized communities. This happens because algorithms can absorb and amplify existing societal biases, a phenomenon she calls algorithmic oppression.

This has manifested in several harmful ways, including reinforcing stereotypes, and perpetuating systemic inequality. Noble's (2018) research showed how searches for "black girls" prioritized pornographic and hypersexualized content, reinforcing damaging historical stereotypes. Similarly, Google's autosuggest feature has completed search queries with racist and sexist phrases, and its image recognition software has notoriously mislabeled black people as gorillas. The bias, however, isn't limited just to search. Algorithms used in the real world have shown similar flaws, like how the judicial algorithm, COMPAS, was more likely to falsely flag black defendants as future criminals than white defendants. With many of the factors going into these algorithms hidden from public view, it's difficult to audit their biases, and thus hold companies accountable.

Algorithms also play a increasing role in shaping my professional life, influencing everything from the jobs I apply for to my ongoing skill development. Platforms like LinkedIn use their own ranking to show me jobs it thinks I'm a good fit for, effectively filtering the opportunities I see. And as many hiring managers begin to rely more on AI-powered Applicant Tracking Systems, these algorithms rank me against other applicants based on its interpretation of resume. Beyond the job hunt, algorithms also guide my professional development. For instance, during the Usability Tool project, I began searching for beginner Figma tutorials on YouTube. Since then, the platform's recommendation engine has begun suggesting not only more Figma content but also related videos on improving UI/UX design and designing for learners, proactively charting a potential path for my growth in these areas.