Fintech Apps in Hong Kong: Data and Speculation in the Face of Precarity
Refereed conference paper presented and published in conference proceedings


摘要In Hong Kong—a colony turned neoliberal testbed—fintech apps (financial technology applications) target those who experience various forms of precarity, such as millennials (i.e. students), elderly housewives, and migrant domestic workers. This paper analyzes their situated experience of datafied finance in terms of the interplay between openness, exposure, enclosure, and foreclosure across the data-centric epistemologies and aesthetics of front-end interfaces and back-end algorithmic systems of data mining and exploitation. For instance, fintech apps promise openness in the sense of transparency and access to financial opportunities by redistributing data-centric perception and cognition. Yet at the same time, they enclose data and foreclose futures by subjecting users to algorithmic credit-scoring and social sorting (Lyon 2003). The reduction through datafication and subjection to AI can however shift into more erratic forms of harm associated with exposure when we consider vulnerability in the face of the ungovernability of data mobilities and the random heteronomic determination of user subjectivity via AI (Lotti forthcoming; MacKenzie 2014; O’Neil 2016; Pasquale 2015; Speculate This! 2013). This paper explores three “classes” of users defined by the opening/enclosing/foreclosing effects of distributions of data-centric perception and cognition. These are the predicting class equipped with robo-advisors; the predicted class that self-identifies through credit-scoring; and the unpredictive class, negotiating exclusion and anonymity. Second, I juxtapose articulations of uncertainty as quantified expression of risk versus as cultural signification and affective experience of precarity. I ask whether and how personal data could conjure publics and tell stories that defy social sorting and foreclosure by recovering the openness of the future while enabling new relations of solidarity. Methodologically, this paper draws on walkthrough methods for app analysis and interviews with fintech designers and users in Hong Kong.
著者HOYNG Rolien Susanne
會議名稱3rd Data Power Conference
會議地點University of Bremen

上次更新時間 2020-26-06 於 10:57