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VIDEO DOI: https://doi.org/10.48448/9rc9-sf54

technical paper

AAA Annual Meeting 2021

November 18, 2021

Baltimore, United States

A Moonshot for Mental Health Care in Canada: Building a BrainHealth Databank We Can Trust


science & technology studies

applied anthropology

big data

This panel opens a discussion about forms of collaboration between anthropologists and data scientists. Anthropologists have recently turned to the study of data and algorithms, offering critical insights about their production and implementation. They have addressed the effects of algorithmic automation (e.g. increasing surveillance, inequality exacerbation, new forms of discrimination) and conducted fieldwork among data scientists in order to bring the socio-cultural dimensions of their work to the forefront. However, these efforts rarely alter the practices of data science and the boundaries between disciplines have remained durable. This panel asks: How can anthropology make an impact on data science? Can the relationship between anthropology and data science be reconfigured? How can anthropologists remain, as Marilyn Strathern has suggested, ‘a community of critics’ while also engaging affirmatively with data scientists and interfering productively with their epistemic practices? Beyond understanding the data scientist’s point of view and destabilizing our own disciplinary habits and assumptions, this panel asks if there may be other ways to collaborate. Is it possible, for example, to set up experiments that straddle disciplinary boundaries and craft shared spaces of practice? How can we facilitate the envisioning of productive, inclusive, just and diverse future scenarios? Practicing anthropology as a study with people rather than a study of people, this panel welcomes papers that, not only discuss and criticize ‘data cultures,’ but also share experiences and explore and speculate on innovative forms of collaboration between data scientists and anthropologists in various fields (e.g. market analysis, design and development of products and services, computational biology, personalized medicine, epidemiology, engineering etc.).


Transcript English (automatic)

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