Google

How Does Searching on Google Work

According to Google, the search engine works through three stages:

“Google Search works in three stages, and not all pages make it through each stage:

1. Crawling: Google downloads text, images, and videos from pages it found on the internet with automated programs called crawlers.

2. Indexing: Google analyzes the text, images, and video files on the page, and stores the information in the Google index, which is a large database.

3. Serving search results: When a user searches on Google, Google returns information that's relevant to the user's query.” (How Search works for site owners)

These are typical functions of search engines.

However, it’s important to note that Google, as efficient and all-knowing as it claims to be, is not a neutral conductor of information. As Safiya Umoja Noble reminds us in her book Algorithms of Oppression, “While we often think of terms such as ‘big data’ and ‘algorithms’ as being benign, neutral, or objective, they are anything but. The people who make these decisions hold all types of values, many of which openly promote racism, sexism, and false notions of meritocracy, which is well documented in studies of Silicon Valley and other tech corridors” (2018). Though many of Google’s products and services operate through algorithms, it is necessary to remember that there are real people both behind the creation of this coding and on the receiving end of the algorithm’s output.

Furthermore, algorithms do not exist within a vacuum, for algorithmic results translate to real world effects, real world ideologies. Quadflieg et al. (2022) assert

. . . computers are ubiquitously integrated into our physical environment and not even always recognizable as computers. This new kind of computer use is all-encompassing: It affects our private lives as well as major societal developments—computers and the algorithms that work within them have an impact on our lives whose dimension is almost impossible to grasp.

Algorithms must be considered more analytically and less passively by both users and Google employees.

When using Google’s search engine, it’s important to consider how you, the user, are giving up your own information. Google explains that it “uses the information shared by sites and apps to deliver our services, maintain and improve them, develop new services, measure the effectiveness of advertising, protect against fraud and abuse, and personalize content and ads you see on Google and on our partners’ sites and apps” (How Google Uses Information from Sites or Apps that Use our Services). Google describes their data collecting practices in a way that rhetorically mimics care and concern for its users. What Google often leaves out is the passive collection of data, often happening without users’ knowledge and active participation or consent. In a 2018 study performed by Professor Douglas C. Schmidt of Vanderbilt University, it was found, among many other things, that

Google learns a great deal about a user’s personal interests during even a single day of typical internet usage. In an example “day in the life” scenario, where a real user with a new Google account and an Android phone (with new SIM card) goes through her daily routine, Google collected data at numerous activity touchpoints, such as user location, routes taken, items purchased, and music listened to. Surprisingly, Google collected or inferred over two-thirds of the information through passive means. At the end of the day, Google identified user interests with remarkable accuracy.

Sure, Google having the power to know about an individual’s daily routine may seem creepy, but ultimately harmless; however, Google’s ability to know about billions of people is terrifying, and ultimately transcends beyond the bounds of search tools and into “instruments of surveillance” (Quadflieg et al., 2022).

Rather than simply taking Google’s algorithm for granted, users should resist and reject the automation of collected personal information. Giving away data has become readily accepted, if not wholly ignored. Manovich explains that “recommendation engines suggesting what we should watch, listen to, read, write, or wear; devices and services that automatically adjust the aesthetics of captured media to fit certain criteria” are certainly biasing choice, but this type of automated suggesting is also dangerous to the ways in which our culture is shaped.

While Google may never cease to exist in such a large technological capacity, users can actively resist Google’s data collection by opting out of these services, as well as making others aware of the risks associated with population-wide data surveillance.

Of course, it’s also important to consider what results are being returned. These results are heavily dependent on one’s collection of data, for your location and browser history influence what results you see, but Google search results are also ingrained with bias and discrimination, historically regarding gender and sexuality (Baker & Potts, 2013; Noble, 2018; Dill, 2022).

Overall, Google is biased in ways that increase its own profits. Whether that be through surveillance methods, such as location pinging, or profile-building methods, such as automated suggestions or search results that resemble your browser history, Google is selling (and solidifying) itself as the most-used search engine. However, its popularity should not distract users from the inherent bias and discrete data collection ingrained in Google’s search engine. Users must take an active stand against Google's predatory methods.

Takeaways

• Google is not a neutral site of information.

• Google is harvesting and using your information (whether you know it or not).

• Users must educate themselves and others about the repercussions of using Google’s search engine, such as data collection and biased search results, for “algorithmic oppression is not just a glitch in the system but, rather, is fundamental to the operating system of the web. It has direct impact on users and on our lives beyond using Internet applications” (Noble 2018).