Reading Group #2 on 'Introduction to Seminar Theme: Hidden Labour (Part I)'
Wednesday 17 June 2020, 15:00–17:00 BST
Overview
Co-facilitator: Prof. Matteo Pasquinelli (University of Arts and Design Karlsruhe)
Discussants: Audrey Borowski (University of Oxford), Cindy Lin (University of Michigan, Ann Arbor)
Moderator: Prof. Matthew L. Jones (Columbia University)
Readings:
- Daston, Lorraine (2018). 'Calculation and the Division of Labor, 1750-1950'. Bulletin of the German Historical Institute, 62 (Spring), 9-30.
- Pasquinelli, Matteo (forthcoming). 'The Material Tools of Algorithmic Thinking', chapter 1. The Eye of the Master. London: Verso.
Matteo Pasquinelli is professor at the University of Arts and Design Karlsruhe. Prof. Pasquinelli coordinates the research group on media philosophy and artificial intelligence KIM. With Vladan Joler, he recently published the visual essay 'The Nooscope Manifested: AI as Instrument of Knowledge Extractivism'. For Verso, he is preparing a book titled The Eye of the Master on the history of AI as the automation of labour, of its vision and division.
A summary of the Hidden Labour theme is available here. Prof. Pasquinelli provides the following overview of the session:
The Hidden Intelligence of Labour: For a Social History of Algorithms
Different genealogies of artificial intelligence can be read on the shoulders of workers, merchants, bureaucrats and spies. AI emerged as the project to automate tasks that, since WWII, have ranged from image recognition and object manipulation, to stock price negotiation, and the analysis of public and military datasets.
This overview retraces a canonical genealogy of AI from within the milieu of the industrial revolution and early political economy. Daston (1994, 2017), Schaffer (1994), and Jones (2016) have shown that the project of machine intelligence emerged from the industrial automation of mental labour as hand calculation (Babbage, 1832) rather than the mere dream to forge 'thinking automata.' The design of intelligent algorithms imitated, then, the 'analytical intelligence' (Daston, 2018) of the division of labour. This intuition can be expanded, today, to interrogate in which way the algorithms of machine learning automate sophisticated forms of manual, mental and visual labour by encoding an extended division of space, time and social behaviours.
In order to understand the relation between AI and labour, it would be useful to clarify first the relation between the algorithm form and the division of labour. From the point of view of invention and knowledge production, which one comes first? Knuth (1972) attempted a historicisation of the algorithm in the essay 'Ancient Babylonian Algorithms.' At the time, Knuth aimed at systematising the new field of computer science and to make it into a respectable academic and industrial discipline (Ensmerger, 2010). The idea of the ancient algorithm was mobilised to stress that the new field of computer science was not about obscure machinery but part of a long tradition of cultural techniques of symbolic manipulation. On their side, historians of mathematics such as Chabert (1999), Damerow and Lefèvre (1981) have clarified the genesis of mathematical abstractions in the relation of labour with material tools. Also these approaches can be used to interrogate computation and AI as a solution to the problem of the management of labour, or, from another angle, to recognize the hidden intelligence of labour building the algorithm from within.
References
- Babbage, Charles (1832). On the Economy of Machinery and Manufactures. London: Charles Knight.
- Chabert, Jean-Luc, ed. (1999). A History of Algorithms: From the Pebble to the Microchip. Berlin/New York: Springer.
- Damerow, Peter, and Wolfgang Lefèvre, eds. (1981). Rechenstein, Experiment, Sprache: Historische Fallstudien Zur Entstehung Der Exakten Wissenschaften. Stuttgart: Klett-Cotta.
- Daston, Lorraine (1994). 'Enlightenment Calculations'. Critical Inquiry 21, no. 1: 182-202.
- Daston, Lorraine (2018). 'Calculation and the Division of Labor, 1750-1950'. Bulletin of the German Historical Institute, 62 (Spring), 9-30.
- Ensmenger, Nathan (2010). The Computer Boys Take Over: Computers, Programmers, and the Politics of Technical Expertise. Cambridge, MA: MIT Press.
- Jones, Matthew L. (2016). Reckoning with Matter: Calculating Machines, Innovation, and Thinking About Thinking from Pascal to Babbage. Chicago: Univ. of Chicago Press.
- Knuth, Donald E. (1972). 'Ancient Babylonian Algorithms'. Commun. ACM 15, no. 7: 671–77.
- Schaffer, Simon. (1994). 'Babbage's Intelligence: Calculating Engines and the Factory System'. Critical Inquiry 21, no. 1: 203-27.
Summary of event
Pasquinelli questioned how to define hidden labour, with reference to:
- The division of labour which AI and machinery come to produce;
- The supervision and evaluation of a machine operator;
- The vast, submerged labour of care and support required in AI automation.
With reference to Daston's thesis, he outlined the need for:
- A labour theory of machine intelligence
This pertains to 19th century political economy, allowing questions such as 'who owns labour?' to arise, i.e. a horizontal division of labour. - A class theory of machine intelligence
This pertains to a not just horizontal but vertical division of labour, in which 'skilled' labour is made visible, and 'unskilled' labour is made invisible, leading to the rendering of workers as mechanical/automated before their actual replacement. This is particularly relevant to forms of racialised and reproductive labour.
Borowski's presentation related to her work on Leibniz as part of her D.Phil. She questioned the philosophical perfection of a human mind in God's image in line with a genealogical analysis of mathematics and rationality.
Lin's presentation related to her ethnographic PhD research into the development of DevOps in an engineering agency in the postcolonial state of Indonesia. Her provocations included: (i) the need to understand the military and colonial relations of 'shipping' software as analysis of DevOps 'containers' and (ii) the new division of labour which may arise from promises of inexhaustibility of software containerisation.
Works cited (in the chat)
Labour, Infrastructure, Software:
- 'Exchanges with Turkers', n.d.
- 'Logistical Worlds: Infrastructure, Software, Labour', n.d.
- 'Submarine Cable Map', n.d.
- Gregg, Melissa. Counterproductive: Time Management in the Knowledge Economy. Durham: Duke University Press, 2018.
- Moreschi, Bruno, Gabriel Pereira, and Fabio G. Cozman. 'The Brazilian Workers in Amazon Mechanical Turk: Dreams and Realities of Ghost Workers'. Revista Contracampo 39, no. 1 (17 April 2020).
- Posner, Miriam. 'See No Evil', 1 April 2018.
- Puar, Jasbir, ed. 'Precarity Talk: A Virtual Roundtable with Lauren Berlant, Judith Butler, Bojana Cvejić, Isabell Lorey, Jasbir Puar, and Ana Vujanović'. TDR/The Drama Review 56, no. 4 (December 2012): 163–77.
- Suchman, Lucille Alice. Human-Machine Reconfigurations: Plans and Situated Actions. 2nd ed. Cambridge; New York: Cambridge University Press, 2007.
History, Violence, Resistance:
- Almond, Ian. History of Islam in German Thought: From Leibniz to Nietzsche. 1st publ. in paperback. Routledge Studies in Cultural History 11. New York, NY: Routledge, 2011.
- Davies, Thom. 'Slow Violence and Toxic Geographies: "Out of Sight" to Whom?' Environment and Planning C: Politics and Space, 10 April 2019.
- Fisher, Anna Watkins. The Play in the System: The Art of Parasitical Resistance. Durham: Duke University Press, 2020.
- Nixon, Rob. Slow Violence and the Environmentalism of the Poor. 1. Harvard Univ. Press paperback ed. Cambridge, Mass.: Harvard Univ. Press, 2013.
Boundaries of Technical Practice:
- Hoffmann, Anna Lauren. 'Where Fairness Fails: Data, Algorithms, and the Limits of Antidiscrimination Discourse'. Information, Communication & Society 22, no. 7 (7 June 2019): 900–915.
- Jordan, Michael I. 'Artificial Intelligence – The Revolution Hasn't Happened Yet', 1 July 2019.
- Marcus, Gary. 'Deep Learning: A Critical Appraisal'. ArXiv:1801.00631 [Cs, Stat], 2 January 2018.
- Marcus, Gary, and Yann LaCun. 'Debate: "Does AI Need More Innate Machinery?"' 5 October 2017.
- Mindell, David A. Between Human and Machine: Feedback, Control, and Computing Before Cybernetics. Johns Hopkins Studies in the History of Technology. Baltimore: The Johns Hopkins University Press, 2002.
- Roff, Heather. 'How Understanding Animals Can Help Us Maximize Artificial Intelligence'. The Conversation, 2 April 2017.
- Watson, David. 'The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence'. Minds and Machines 29, no. 3 (September 2019): 417–40.
- Weizenbaum, Joseph. Computer Power and Human Reason: From Judgment to Calculation. San Francisco: Freeman, 1976.
Class, Capitalism, Gender:
- Crary, Jonathan. 24/7: Late Capitalism and the Ends of Sleep. London: Verso, 2014.
- Dillon, Sarah. 'The Eliza Effect and Its Dangers: From Demystification to Gender Critique'. Journal for Cultural Research 24, no. 1 (2 January 2020): 1–15.
- Haritaworn, Jinthana, Adi Kuntsman, and Silvia Posocco. Queer Necropolitics, 2015.
- Indira Ganesh, Maya, and Johannes Bruder. 'Cloud Cosmogram', n.d.
- Nakamura, Lisa. 'Prospects for a Materialist Informatics: An Interview with Donna Haraway'. Electronic Book Review, 30 August 2003.