Talk: The Return of the Social: Algorithmic Identity in an Age of Symbolic Demise, Dan Kotliar, Dept. Sociology and Anthropology, the Hebrew University of Jerusalem.
Title: The Return of the Social: Algorithmic Identity in an Age of Symbolic Demise
Based on an ethnographic study of the Israeli data analytics scene, this presentation explores the socio-algorithmic construction of identity categories. While algorithmic categorization has been described as a post-textual, or post hegemonic phenomenon that leaves language, theory, and expertise behind, this article focuses on the return of the social – the process through which the symbolic means resurface to turn algorithmically-produced clusters into identity categories. I argue that such categories not only stem from the intrinsic structure of the algorithms and their data, but from the social contexts in which they arise, and particularly, from the values assigned to them by the people who buy and use them. I accordingly show that the return of the social is more than a process of translation, but of a complex amalgamation, which arbitrarily conjoins algorithmic clusters with qualitative labels, in an attempt to answer to people’s wants and needs. Finally, I argue that the qualitative stages behind this naming process are just as opaque, and just as black boxed, as the calculative ones.
Dan Kotliar is a PhD Candidate at the Department of Sociology and Anthropology, the Hebrew University of Jerusalem. Dan holds an MA in Anthropology (summa cum laude) from the University of Haifa. He has published on depression narratives in blogs, and on the political construction of emotions in the Israeli-Palestinian context. The latter article won the best article prize of the Israeli Sociological Association in 2017. Dan teaches a course on the ethical and social implications of Data Science and AI, and is a member of the Israeli National Committee for AI ethics. His dissertation, under the guidance of prof. Eva Illouz, is titled "The Algorithmic Construction of Contemporary Consumers: Data Mining and Online Profiling".