Hello I’m Ryan Cowan and this is my guide on how to be an ethical and just digital citizen. You may ask what makes up a digital society first of all, and that would be the governments, corporations, and the people of the world connected to the internet. The roles of the governments and corporations are supposed to be to use this data for good to improve and advance our overall society, and the people’s job is to provide the data (whether that be through search history, cookies, surveys, etc.) and keep the governments and corporations in check and doing their job in providing for the people (goods, jobs, infrastructure improvement, etc.). In being an individual citizen one of our biggest jobs is to challenge power. A lot of data is collected now through artificial intelligence and computers which was developed by some of the most powerful people (typically being white elites) heading corporations and governments and has been inherently racist. For example in the Data Feminism reading for this lab the author brings up a questionnaire given to prisoners assessing their risk factor saying, “Although
the questionnaire does not ask directly about race, it asks questions that, given the
structural inequalities embedded in US culture, serve as proxies for race. These include
questions like whether you were raised by a single mother, whether you have ever
been suspended from school, or whether you have friends or family that have been
arrested. In the United States, each of those questions is linked to a set of larger social,
cultural, and political— and, more often than not, racial— realities.”
Like the author pointed out these surveys that assess off of questions clearly affecting one demographic to a much more severe degree hurts not only the stereotype being affected, but the people who will be hurt in the future off of mislabeling a white person who is assessed as a low risk prisoner and gets out early and commits a crime. In being a digital citizen this commitment to holding the people in power accountable we are working towards removal of harmful stereotypes from data that help end cycles of oppression on marginalized communities. For example in the Data Feminism article the author mentioned the main point of creating studies like Local Lotto it helps educate marginalized communities on how when you start behind in life it’s much harder to come back versus when your ahead like many of these corporate elites have been. But, while that is an uncomfortable truth the program also harped and actively taught the way to end that cycle is through education. Just like in the first Braiding Sweetgrass essay when Laurie presents her first thesis to the Dean on harvesting sweetgrass saying, “The dean looked over the glasses that had slid down his nose, fix–
ing Laurie with a pointed stare and directing a sidelong glance toward
me. “Anyone knows that harvesting a plant will damage the population.
You’re wasting your time. And I’m afraid I don’t find this whole tradi–
tional knowledge thing very convincing.” Like the former schoolteacher
she was, Laurie was unfailingly calm and gracious as she explained fur–
ther, but her eyes were steely.”
This questioning of the common practice of a higher structure is something that is essential as a digital citizen, after this she went out to prove the Dean wrong and put the practices passed down to her into actual scientific data proving the way that the scientific field held as the standard for farming Sweetgrass based off of their data was in fact wrong and that traditional practices that have held up over time will work.