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The Objective Function: Science And Society In The Age Of Machine Intelligence, Emanuel D. Moss
The Objective Function: Science And Society In The Age Of Machine Intelligence, Emanuel D. Moss
Dissertations, Theses, and Capstone Projects
Machine intelligence, or the use of complex computational and statistical practices to make predictions and classifications based on data representations of phenomena, has been applied to domains as disparate as criminal justice, commerce, medicine, media and the arts, mechanical engineering, among others. How has machine intelligence become able to glide so freely across, and to make such waves for, these domains? In this dissertation, I take up that question by ethnographically engaging with how the authority of machine learning has been constructed such that it can influence so many domains, and I investigate what the consequences are of it being …
Dating Apps, Or, Ghosts In The Viral Affect Machine, Gregory Narr
Dating Apps, Or, Ghosts In The Viral Affect Machine, Gregory Narr
Dissertations, Theses, and Capstone Projects
This dissertation is an investigation into the effects of the popularization of dating apps on their users. I use OkCupid, Tinder, and Bumble as paradigmatic examples to flesh out these effects. The data I used for this investigation are fifty interviews and a content analysis of Bumble, Tinder, and OkCupid subreddit forums. I focused on the effects of swiping, texting, and the black boxing of the algorithm in chapters 2, 3, and 4 respectively. In all three chapters, I make the case that the shift to apps conforms with the exigencies of an economy that increasingly makes use of affect …
When Misclassification Is Misgendering: Gender Prediction In The Context Of Trans Identities, Sean Miller
When Misclassification Is Misgendering: Gender Prediction In The Context Of Trans Identities, Sean Miller
Dissertations, Theses, and Capstone Projects
As a subdomain of author profiling, gender prediction (sometimes called gender inference) has received a substantial amount of attention—both as a task in itself, and for other downstream analyses. Throughout the existing literature various statistical and machine learning methods have been applied to extract features in order to either characterize and differentiate female and male writing styles, or simply to achieve maximum accuracy on gender prediction as a binary classification task. However, researchers often do not disclose how they conceptualize gender nor do they consider the implications that gender prediction has for non-binary and trans individuals. Along with an overview …