The Quantification of Love and Lust: Algorithmically Shaping Intimate Relationships on Dating Apps

• In Event: 1555 - Section on Science, Knowledge, and Technology Refereed Roundtables (1 hour)
  In Refereed Roundtable 60min: 1. Artifacts and Politics

Abstract

Dating apps, such as Tinder, OkCupid, and Hinge, have received significant attention in the popular media, but the academic literature has largely overlooked the impact of this technological phenomenon on intimate relationships. In this paper, I draw on the insights from queer theory and apply them to the core programming and functioning of dating apps, which draw on machine learning algorithms to extract patterns and match potential partners. How are the design choices in dating apps shaping intimate relationships at a collective level? Following in the footsteps of Berlant and Warner (1995), this paper asks what does queer theory teach us about the consequences of using algorithmic decisionmaking to predict sexual and romantic preferences? Specifically, what are the assumptions behind dating apps and their academic corollaries, such as the Kosinski and Wang study that claimed to detect sexual orientation through facial recognition software? By providing detailed case studies of a number of dating apps, this piece contributes to analysis of the culture in an algorithmically mediated age.

Author

• Renata Barreto, Berkeley Law