Big Data AI, the Interweb, and Political Affordances

• In Event: Understanding Digital Culture: Useful Tools and Inevitable Elisions

Abstract

Building off earlier work analyzing the political implications of network affordances and social media (Gray & Lopez 2014) and of big data pragmatics and power (Gray 2014), this paper argues that Big Data AI (AI learning from large data sets of human behavior in this case) has shifted much of the interweb’s structure in ways that allow hierarchical organizations to exert real political power. The commercialization of Big Data AI behavioral demographics (including individual targeting) has been weaponized for political cyber-operations by state and non-state actors. The margin of profit is the margin of power. A number of analytic frames are deployed: protocols, algorithms, and especially affordances in order to understand the relationship between network topographies, political power, and agency. Despite its limited physical network and the role of governments and portals, the interweb (network of digital networks) used to be characterized by forces of decentralization (packet switching, peer email, net neutrality) but profit seeking has created mass surveillance and analytics effective enough to shape political realities. Future regulatory regimes, hardware systems, neo-AI programming, protocols, algorithms, and social media platforms, tax systems and so much more are all political issues crucial for shaping the heavily digitized culture of the future. Will it be hierarchical? Horizontalist? Or (most likely) some kludge in-between?

Keywords: Big Data AI, Affordances, Protocols,Algorithms

Gray, Chris Hables (2014) “Big Data, Actionable Information, Scientific Knowledge and the Goal of Control,” TeknoKultura, Vol. 11/no. 3, 529-54.

Gray, Chris Hables and Angel Lopez (2014) “Social Media in Conflict: Comparing military and social movement technocultures,” Cultural Politics, vol. 10/3, pp. 251-61.

Author

• Chris Hables Gray, Crown College, UCSC