At a time when the federal government was first seen shifting its priorities to create the basis of a welfare system, there was also the inescapable question of who is deserving of these new rights and benefits. Franklin Roosevelt not only failed to address the difficulties that Black Americans faced, but he also continued the institutionalization of racism with federal government policies. Roosevelt rejected the proposal to abolish the poll tax and declare lynching a crime. But the most visible codification of racism in federal law came with the removal of domestic workers and farm laborers from the provisions of the Social Security Act.1
Although, the Long Civil Rights movement and the popular front impacted the 1930s by helping create a more equitable society for the marginalized when the federal government failed to do so. The activists from the LCRM and the popular front fought to expand the nation’s immaterial boundaries of who is a citizen worth fighting for and I would argue that this is the same struggle that digital activists are fighting today. Marginalized groups are still scrutinized and discriminated against, except this time it’s less identifiable who’s doing the discrimination and how.
Safiya Noble argues that the “traditional misrepresentations in old media are made real once again online and situated in an authoritative mechanism that is trusted by the public: google.”2. Noble’s keyword search of “black girls” represents how algorithms can perpetuate harmful misrepresentations and the dehumanization of people.3 Despite the fact that marginalized groups are the ones who are being exponentially affected by Google, I would argue that this is a human rights issue that everyone should be concerned about. Anyone using the internet today, whether a target of the state or not, is trading in their privacy, personal information, and most importantly their immaterial labor.
As of right now, the general public is not aware of how algorithms are made and there is a common assumption that the mathematical language of the algorithm would be a barrier to understanding it. Yet, the foundation and design of algorithms can be understood without having to learn a mathematical language. According to Cathy O’Neil, to build an algorithm you need a historical data set and a definition of success. At its core, those are the only two things that need to be understood to get a general grasp of algorithms. Algorithmic literacy must be taught to the public in order to transform artificial intelligence into a less problematic and dangerous entity.
- “Equal Rights and the New Deal,” in The American Yawp, http://www.americanyawp.com/text/23-the-great-depression/#XII_Equal_Rights_and_the_New_Deal
- Safiya Noble, Algorithms of Oppression (New York: Univeristy Press, 2018), 32
- Noble, 19-21
