The role of digital platforms in everyday life is a concern within different research fields; therefore, several authors have supported the need to investigate them and their underlying meshing of human and computational logic. In this chapter, the authors present a methodological proposal according to which auto-ethnographic diaries can be fruitfully employed to examine the relationship between individuals and algorithmic platforms. By drawing on a critical pedagogy approach, they consider auto-ethnography both as a practice of access to algorithmic logics through rich first-hand data regarding everyday usage practices as a response to datafication. The core idea behind this narrative method is to use inductive self-reflexive methodological tools to help individuals critically reflect on their daily activities, thereby making their consumption of algorithmic contents more aware and allowing researchers to collect in-depth reports about their use of digital platforms and the following processes of subjectification.
TopIntroduction
In the last years platforms have emerged as a fundamental business model for companies (Srnicek, 2017) and as the main gateway to the Web for individuals, thereby penetrating every aspect of societies (van Dijck et al., 2018). Specifically, the distinction between the online and offline worlds have become increasingly blurred (Lupton, 2015) and the realm of everyday life has been deeply permeated by the intervention of algorithmic outputs, which continuously select, filter and frame information for us, while shaping what we are able to do on and off our digital devices (Gillespie, 2015). Indeed, if we focus on our ordinary experience, we will easily notice to what extent human life is today deeply intertwined with algorithmic media (Airoldi and Rokka, 2019). How individuals pick movies to watch or songs to listen, how they choose what to eat or which gifts to buy, the ways in which they find out about themselves, their family and friends, but also the partners with which they sleep, are increasingly the result of an algorithmic “production of prediction” (Mackenzie, 2015). In this scenario, platforms emerge as “performative intermediaries”, that actively participate to the co-production of social life “they only purport to represent (Bucher, 2018: 1). Indeed, the affordances that shape and limit how users can act on platforms (Davis, 2020), the processes of categorization (Cheney-Lippold, 2011) and the outputs that intervene in our experience are far from being unbiased and neutral (Airoldi, Gambetta, 2018) and may incorporate socio-cultural biases and result in new forms of digital data discrimination (Angwin et al, 2016; Noble, 2018).
Within this framework, how is it possible to investigate algorithmic media and their crucial and multifaceted role in shaping everyday life and human experience? Although computational procedures are often deemed as “black boxes” that are difficult to unpack (e,g, Pasquale, 2015), recently, several authors highlighted that it is necessary to go beyond that metaphor (e.g. Bucher, 2016; Bonini, Gandini, 2019) and to investigate the social and cultural constructs that lie behind algorithmic infrastructures (Seaver, 2013; Beer, 2017) and the intertwinement between algorithmic media and everyday experience (Bucher, 2018). Furthermore, it has been supported that awareness regarding the intervention of platforms in multiple realms of social life should be risen among citizens (Markham, 2019).
Yet it is questions of method that concern scholars. This contribution supports that ethnography, and especially auto-ethnography, can be a valuable method to investigate “the social power of algorithms” (Beer, 2017) and to build awareness regarding datafication processes, thereby making individuals “critical interpretive researchers of their own lived experience” (Markham, 2019: 794). Thus, an account of a methodological proposal, based on ongoing empirical study, will be presented.