Critical Internet Geographies

(3 Credit Hours) · Undergraduate

In 1996, John Perry Barlow's "A Declaration of the Independence of Cyperspace" framed "the frontiers of Cyberspace" as an apolitical, borderless space where "our identities have no bodies." The invention of the World Wide Web and the continued evolution of internet technologies have drastically changed the norms for communication and community formation. However, internet technologies and platforms have also amplified and magnified deeply-embedded structures of discrimination and oppression. From the Ku Klux Klan's creation of the Aryan Nations Liberty Net in the 1980s to the 21st-century #GamerGate campaign's targeted harassment of women in the video game industry. At the same time, internet technologies and platforms have supported and facilitated the work of activists, advocates, and grassroots organizers. This course moves beyond techno-optimism to critically examine the historical, cultural, social, and political significance of "the internet," from alternate internet histories to contemporary debates around regulation and access. Class meetings will be split between discussions of conceptual readings and applied work with internet technology systems. Readings for this course will draw on texts that include Janet Abbate's Inventing the Internet (1999), Lisa Nakamura and Peter Chow-White's Race After the Internet (2012), Safiya Umoja Noble's Algorithms of Oppression: How Search Engines Reinforce Racism (2018), Charlton McIlwain's Black Software: The Internet and Racial Justice, From the AfroNet to Black Lives Matter (2020), Marisa Elena Duarte's Network Sovereignty: Building the Internet Across Indian Country (2017), Jessie Daniels's Cyber Racism: White Supremacy Online and the New Attack on Civil Rights (2009), Andre Brock Jr.'s Distributed Blackness: African American Cybercultures (2020), and edited collections Race in Cyberspace (Routledge, 2010) and #HashtagActivism: Networks of Race and Gender Justice (MIT Press, 2020). Coursework may include response papers, hands-on work, and a final project. Familiarity with data science or computer science tools and methods is NOT a prerequisite for this course.