Representation (gender, race, culture, orientation)
Building Blocks for Domain of One’s Own: A series of adaptable modules
Interrogating the various identities that impact how one is received and allowed to perform online. Understanding the various racist and sexist underpinnings of supposed neutral platforms and programs.
In groups, conduct the following google image searches and note what trends you see:
– Doctor vs Nurse
– Teacher vs Professor
- What is striking about the image results you found?
- Were you surprised by the results?
- Are these results meaningful? Why or why not?
- If we wanted to alter these results, what would it take?
This week’s discussion may return to some of the same concepts we discussed in the Understanding the Web unit. This time, however, we’re looking at very specific trends that are apparent when searching common terms in Google Image Search. Not surprisingly, the results demonstrate striking representations of race and gender, in particular.
During class discussion, some students may challenge the idea that these search results mean anything or matter very much. This is an opportunity to discuss now societal norms are created and how the internet represents back to us what those norms are. It’s also an opportunity to revisit the discussion of how search works — ultimately, we are seeing the results of an algorithm (coded by Google engineers) as well as the sum total of the content that Google has indexed (from across the Web). Discuss what we have control over (how we represent things on those sites we create) and what we don’t have control over (Google’s algorithms).
Compare the images and language used to describe white defendants in media coverage versus defendants from other ethnic groups. If these news stories are the stuff that feeds the algorithms, what impact does this coverage have on how we view race on the Internet?