In the midst of an ‘unstable era of cognitive–cultural capital accumulation’ (Wyly, 2014), how can computational methods be disentangled from the infrastructures of industry, state, and financial power that reproduce social, economic, and spatial injustice to instead challenge dominant systems of power and exploitation? In these paper sessions, we aim to engage this question through stories of praxis. Taking seriously an intersectional approach to computation requires both (strategically) thinking through the existing computational categories as well as imagining alternative ways of quantifying socio-economic processes and outcomes in line with decolonial, feminist, anti-racist, anti-capitalist, and queer politics. Collectively, we aim to explore the role geographers can play in the radical re-aligning of what constitutes as computation and what becomes known through quantitative data and methods.
We take up social justice broadly defined with intention - not to distill or conquer difference, but in an attempt to generate discussion and reflection towards processes and methods of computation of interest to a range of geographers. Recent work across the social sciences (and outside of academic spheres) exposes various strands of theoretical foundations for computation for social justice - through special issues on ‘Alternative Ontologies of Number’ (de Freitas et al., 2016) and ‘QuantCrit: Critical Race Quantitative Methodologies’ (Garcia et al., 2018), a rich anthology and call for data feminism (D’Ignazio & Klein, 2020), the framing of an ‘Indigenous Protocol and Artificial Intelligence’ (Lewis, Jason Edward, ed., 2020), and ‘A Call for Black Feminist Data Analytics’ in COVID research (COVID Black, 2020), to highlight a few.
Within geography, generative work in critical, feminist, and participatory GIS has enrolled digital technologies, particularly mapping platforms, for social justice. Importantly, these efforts have made ‘othered’ phenomena and stories visible (Anti-Eviction Mapping Project, 2018; Palmer, 2016), centered community participation in mapping (Reid & Sieber, 2020; Ghose, 2001), and prompted re-consideration of entanglements with racialized practices (Jefferson, 2018) and corporate technologies (Alvarez León, 2016; Elwood, 2008). To focus on computational praxis, we draw particular inspiration from scholars working towards social justice by calculating gendered accessibility (Kwan, 2002), challenging racism through critical race spatial analysis (Solorzano & Vélez, 2017), and leveraging opportunity for large-scale data curation (Ehrman-Solberg et al., 2020), as examples. Through these sessions, we aim both to explore emerging computational methods that challenge entrenched power structures and to critically examine computational methods that reproduce and widen inequalities, in order to move towards computational praxis for social justice.
|Presenter||Jin-Kyu Jung*, University of Washington-Bothell, Nora Kenworthy, University of Washington-Bothell, (Un)mapping digital social inequality of health: The COVID-19 and Medical Crowdfunding||15||9:35 AM|
|Presenter||Amir Masoud Forati*, University of Wisconsin - Milwaukee, Rina Ghose, University of Wisconsin Milwaukee, Addressing the opioid crisis in Milwaukee County, WI using data to drive action||15||9:50 AM|
|Presenter||Jeremy Auerbach*, Colorado State University, Solange Munoz, University of Tennessee, Alex Cooper, Child Care Aware of America, Elizabeth Walsh, University of Denver, Analyzing Displacement through Community Vitality||15||10:05 AM|
|Presenter||Megan Raisle, Environmental Data & Governance Initiative, Sara Wylie, Northeastern University, Lourdes Vera, Northeastern University, Kelsey Breseman, Environmental Data & Governance Initiative, Eric Nost*, University of Guelph, Environmental Data & Governance Initiative, , EEW! Computational Praxis and Alternative Infrastructure towards Environmental Data Justice||15||10:20 AM|
|Presenter||Micah Hilt*, , Elvin Wyly*, University of British Columbia, Leveraging A Geography of Virtual Conspiracy||15||10:35 AM|
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