ISSN 1016-1007 GPN2005600032
運算都市生活: 數據實踐與日常生活的轉化 Data Practices and The Transduction of Everyday Life
Sung-Yueh Perng
everyday practices, lifelogging, personal big data, quantified self, transduction, wearable technology
穿戴式科技的普及、自我數值化(quantified self)與生活日誌化(lifelogging)的風行,使得個人日常生活數據的蒐集廣受注目,也激發運算都市生活的多重想像與期望。日常生活的數據蒐集,希望建立全面的、客觀的且持續的個人生活紀錄,以進行對日常生活的運算。著眼於此,本文反思將日常生活數據化的實踐及後果。目前文獻多聚焦在數據實踐的知識生產、社會物質脈絡與政治經濟後果等。本文採取「轉化」的理論取徑,將過去對知識生產的關注,轉移到重新思考數據實踐對日常生活所造成的轉變。

The popularity of wearable technologies and the enthusiasm around quantified self and lifelogging movements have encouraged the collection of personal data in comprehensive, objective, and sustained ways for computing urban life. In light of these emergent data practices, this paper explores and critically reflects upon how such practices are undertaken and what consequences they engender. Most studies in the literature concerned with quantified self and lifelogging have focused their discussion on the practices of knowing, the sociomaterial contexts of knowledge practices, or the political economic consequences of such modes of knowing. The paper thus proposes to understand data practices as an ontogenetic process and analyzes their transduction of everyday life. The paper is based on the research conducted in Dublin and Boston between 2014 and 2016. Building on this empirical research, I demonstrate how wearable technologies and wearers of related products attempt to reconfigure each other when transforming life into data and how this process unexpectedly and unevenly transduces ways in which everyday life is undertaken. What this process has achieved then is not a complete translation of everyday life into data; rather, the parts of life that are easier to record receive more attention and the data about them become enriched and expanded, at the expense of others that are difficult for computing logic to work with. Such uncertain and uneven processes of transduction can complicate any claims and sociotechnical imaginaries of a complete translation of everyday life into data and the computing of such data for engineering better societal futures.