Using machine learning and artificial intelligence, Uber has been disrupting the world taxi industry. However, the Uber algorithmic apparatus managed to perfectionize the scalable decentralized tracking and surveillance of mobile living bodies. This article examines the Uber surveillance machinery and discusses the determinants of its algorithmically powered ‘all-seeing power’. The latter is being figured as an Algopticon that reinvents Bentham’s panopticon in the era of the platform economy.
DanaherJ (2016) The threat of algocracy: Reality, resistance and accommodation. Philosophy and Technology29(3): 245–268.
15.
De StefanoV (2016) The rise of the just-in-time workforce: On-demand work, crowdwork and labour protection in the gig-economy. Comparative Labor Law & Policy Journal37(3): 471–504.
GreenfieldA (2017) Smartphone: The networking of the self. In: GreenfieldA (ed.) Radical Technologies: The Design of Everyday Life. London: Verso Books, p. 359.
26.
HaggertyKD (2006) Tear down the walls: On demolishing the panopticon. In: LyonD (ed.) Theorizing Surveillance: The Panopticon and Beyond. Portland, OR: Willan Publishing, pp. 23–45.
27.
HaggertyKDEricsonRV (2000) The surveillant assemblage. British Journal of Sociology51(4): 605–622.
JamilR (2017) Drivers Vs Uber–The limits of the Judicialization: Critical review of London’s employment tribunal verdict in the case of Aaslam Y. & Farrar J. against Uber. Revue Interventions Économiques. Papers in Political Economy58.
KenneyMZysmanJ (2016) What is the future of work? Understanding the platform economy and computation-intensive automation. BRIE Working Paper 2016-9, December. Berkley Roundtable on the International Economy. Available at: https://brie.berkeley.edu/sites/default/files/brie-wp-2016-9.pdf
LyonD (2006) The search for surveillance theories. In: LyonD (ed.) Theorizing Surveillance: The Panopticon and Beyond. Portland, OR: Willan Publishing, pp. 3–20.
34.
MathiesenT (1997) The viewer society: Michel Foucault’s ‘panopticon’ revisited. Theoretical Criminology1(2): 215–234.
O’NeilC (2016) Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Broadway Books.
38.
PrasslJRisakM (2015) Uber, taskrabbit, and co.: Platforms as employers-rethinking the legal analysis of crowdwork. Comparative Labor Law & Policy Journal37(3): 619–652.
39.
RisakMWarterJ (2015) Legal strategies towards fair conditions in the virtual sweatshop. In: Paper presented at the IV Regulating for Decent Work conference, ILO, Geneva, 8–10 July 2015. Available at: http://www.rdw2015.org/download
40.
RosenblatAStarkL (2016) Algorithmic labor and information asymmetries: A case study of Uber’s drivers. International Journal of Communication10: 3758–3784.
41.
SilbermanMSIraniL (2016) Operating an employer reputation system: Lessons from Turkopticon, 2008–2015. Comparative Labor Law & Policy Journal37(3): 505–541.
42.
SrnicekN (2016) Platform Capitalism. Cambridge: John Wiley & Sons.
43.
StandingG (2011) The Precariat: The New Dangerous Class. London; New York: Bloomsbury Academic.
Uber Data (2017) Engineering more reliable transportation with machine learning and AI at Uber. Uber Engineering, 10November. Available at: https://eng.uber.com/machine-learning/