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Unveiling inequality and (un)doing ethnography of datafied capitalism [Anthropology of Economy Network (AoE)] 
Marie Kolling (Danish Institute for International Studies (DIIS))
Sofie Henriksen (Danish Institute for International Studies)
Pernille Hohnen (Roskilde University)
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Moisés Kopper (University of Antwerp)
Tuesday 23 July, -, -
Time zone: Europe/Madrid
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Short Abstract:

The panel explores contemporary capitalism, datafication and inequality. It also addresses methodological and ethical challenges in 'studying up' and getting access to the black box of regulatory and commercial business models that thrive on AI, algorithmic predictions and big data harvesting.

Long Abstract:

Anthropologists doing fieldwork in data-driven markets have challenged classic ethnographic practices and ethical conventions (Seaver 2017; Bonini and Gandini 2020; Souleles 2020). In order to unveil current state-led and corporate practices of harvesting and commodifying data about people’s social lives, they suggest developing alternative tactical ethnographic techniques and to work with a set of less ‘protective’ ethics. This panel seeks to explore ethnographic research on datafication and contemporary capitalism 1) to discuss concerns with the shortcomings of ethnographic methods and ethical conventions when ‘studying up’ (Nader (1972) and trying to access closed economic fora (Garsten & Sörbom 2018) and 2) to engage in dialogue with critical literature on contemporary capitalisms such as “data capitalism” (Myers West 2019), “surveillance capitalism” (Zuboff 2019), “data colonialism” (Couldry & Mejias 2019), “platform capitalism” (Srnicek 2017), “data extractivism” (Mezzadra & Nielson 2017; Jung 2023) and “digital capitalism” (Burrell & Fourcade 2021). Individuals typically have limited options to opt out from having their data harvested, data that in turn is processed to determine the services that are offered or denied, often producing new or reinforcing existing inequalities. Papers may include research on for-profit and non-profit data-based interventions addressing inequalities in areas such as insurance, banking, and development aid. We invite papers discussing implications of current data practices and data-driven business models that are notoriously hidden from public view, and also reflecting upon methodological and ethical challenges of accessing and conducting research on the “black box” of algorithmic decisions and digital infrastructures.

Accepted papers:

Session 1 Tuesday 23 July, 2024, -
Session 2 Tuesday 23 July, 2024, -