Algorithmic Injustice: How Data Ethics Enable More Harmful Data Practices

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