A panel session at the Association of American Geographers Annual Conference, San Francisco, March/April 2016. Organized by Andrea Miller (UC Davis) and Jeremy Crampton (Kentucky).
“It’s time for government to enter the age of big data. Algorithmic regulation is an idea whose time has come.” Tim O’Reilly.
This panel will address the increasing concern and interest in what we here label “algorithmic governance.” Drawing on Foucault’s governmentality and Deleuzian assemblage theory, as well as the nascent field of critical Big Data studies, we are interested in investigating the manifold ways that algorithms and code/space enable practices of governance that ascribes risk, suspicion and positive value in geographic contexts.
This value often takes the form of money. For instance, Facebook’s average revenue per user (ARPU) in Q2 2015 was $2.76 globally and as much as $9.30 in North America, while, according to Apple, there are over 680,000 apps using location on iOS. However, pecuniary value derived from spatial Big Data must also be understood as inseparable from capacities of risk and suspicion simultaneously generated and distributed through data-driven relationships. More generally, the purpose of these data is two-fold. On the one hand, they allow risk and threats to be managed, and on the other hand, by drawing on these new subjectivities, they increasingly generate new modes of prediction and control. Thus, algorithmic life can be understood as “data + control,” or to use a Foucauldian term, “data + conduct of conduct,” or what we can call “algorithmic governance.”
Following Rob Kitchin’s suggestion that algorithms can be investigated across a range of valences—including examining code, doing ethnographies of coding teams or geolocational app-makers, and exploring algorithms’ socio-technological material assemblages (Kitchin, 2014), we convene this panel to explore some of the following questions in a spatial or geolocational register:
- How can we best pay attention to the spaces of governance where algorithms operate, and are contested?
- What are the spatial dimensions of the data-driven subject? How do modes of algorithmic modulation and control impact understandings of categories such as race and gender and delimit the spatial possibilities of what Jasbir Puar has called the body’s “capacity” for emergence, affectivity, and movement (Puar, 2009)?
- Are algorithms deterministic, or are there spaces of contestation or counter-algorithms?
- How does algorithmic governance inflect and augment practices of policing and militarization?
- What are the most productive theoretical tools available for studying algorithmic data, and can we speak across the disciplines?
- How are visualizations such as maps implicated by or for algorithms?
- Is there a genealogy of algorithms that can be traced prior to current forms of technology (to a more “proto-GIS” era for example)? How does this tie with other histories of computation?
Kitchin, R. 2014. “Thinking Critically About and Researching Algorithms.” Programmable City Working Paper 5. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2515786
O’Reilly, T. 2013. “Open Data and Algorithmic Regulation.” In B. Goldstein and L. Dyson (Eds)., Beyond Transparency. San Francisco: Code for America Press. http://beyondtransparency.org/chapters/part-5/open-data-and-algorithmic-regulation/
Puar, Jasbir. 2009. “Prognosis Time: Towards a Geopolitics of Affect, Debility and Capacity.” Women and Performance, 19.2: 161-172.