@article{THESIS,
      recid = {3078},
      author = {Majnoni d'Intignano, Fosca},
      title = {Algorithmic Injustice: How Data Ethics Enable More Harmful  Data Practices},
      publisher = {University of Chicago},
      school = {M.A.},
      address = {2021-08},
      number = {THESIS},
      abstract = {Drawing on primary source documents, interviews, and  secondary sources, this paper aims to provide a provocative  evaluation and critical investigation into the social,  economic, and technological processes informing the current  conversation surrounding the development of data ethics  within big data corporations and the social media industry.  While there has been a rapid proliferation of academic and  professional studies on the ethics of data in recent years,  many studies assume that the social harms of big data can  be alleviated by aligning AI and ML with human ethics.  Using ideas that are rooted in an anthropological stance,  this paper argues that universal human ethics do not and  never will exist. I explore contradictions arising from the  way in which the discussion concerning data ethics is  guided and dominated by big data corporations like Google,  whose dubious data-related practices can be seen as merely  a kind of “ethics-washing” in the service of positive  corporate branding. On the other hand, I consider the  paradox whereby data ethics assumes that an ethically  flawed society can create machinic systems that operate  ethically. I maintain that we should not aim for a perfect  AI world of ideal machinic ethics but rather for a system  of ethically imperfect humans working with ethically  imperfect machines toward a mutual development of a better  society.},
      url = {http://knowledge.uchicago.edu/record/3078},
      doi = {https://doi.org/10.6082/uchicago.3078},
}