Description

From mechanical looms in the 19th century to generative AI tools in the 21st, labor-saving technology has always provoked warnings of accelerating exploitation—and, at the same time, visions of a future society freed from drudgery. We will call on central texts and concepts in Science, Technology, and Society to help us understand how automation and AI have been proposed, implemented, and resisted within specific working contexts. Hype and criticism alike tend to treat automation as a universal technological phenomenon. We will see that automation and AI have actually meant many different things in different moments and settings. In this project-centered course, students will learn to analyze particular forms of work and anticipate how they might next incorporate or reject cutting-edge technology.

Learning objectives

By the end of this course, you should be able to:

  • Use historical understanding to assess claims about automation’s past and predicted effects on work and society
  • Describe the historical context under which automation became a public controversy in the postwar United States
  • Identify relations between technology and labor in your own work, learning, and leisure activities
  • Formulate your own informed opinions about past and future trajectories for automation and AI

Course structure and class structure

This course will organize material into three modules. In our first three weeks, we will discuss automation in general terms and get a broad sense of its historical contours. The following six weeks will take us through a variety of particular contexts in which authors have studied automation’s implementation and effects. In the final six weeks, we will first zoom back out to see how STS frameworks can apply across contexts, then turn toward perspectives that have likewise collected resistant worker perspectives across different settings.

Most weeks have readings assigned for both class meetings, though a few Wednesday sessions will instead be devoted to project preparation. We will spend the bulk of our class time discussing the readings together, guided by your reading responses. Some Monday meetings will feature more talking from me in a mini-lecture format.

Project: scripting and de-scripting automation in context

The course will culminate with a final project in which you apply concepts from our readings and discussions to a context of your choosing. In this two-stage assignment, you will first select a working context and then describe how automation might transform it—from the perspective of an automation planner and from the perspective of a worker strategizing against automation.

In part 1, we will work together in class to brainstorm and identify working contexts at an appropriate scale for the assignment. You will then produce a short written or audiovisual report that identifies: A) how work has historically been organized, observed, and compensated in this context; B) how automation, computers, or other control technologies have so far factored into this work; and C) a particular routine that is essential within this work.

In part 2, each student will write an essay in two subparts: first, drawing on Madeline Akrich’s concept of “scripts,” you will propose how AI or other technology could replace part of the routine you identified in part 1.B. Second, drawing on Akrich’s method of “de-scription,” you will propose a set of tactics by which workers might adjust the routine and the technology to create a situation that planners did not intend.

Weekly reading responses

Your assignment for each day a reading is listed, to be posted to our Canvas page by 9pm the evening before our class meeting, is to:

  1. read the assigned reading(s),
  2. pick a single sentence from one reading that either
    1. confused you the most or
    2. excited you the most; then,
  3. type out the sentence and note the page number, and
  4. as briefly as possible, explain
    1. why, in your own words, understanding this sentence should help us understand what the author wanted to accomplish with this piece, and
    2. why it confused/excited you.

Some elaboration on the above:

  • A and B don’t always need to be different things—it could be the case that the most confusing and exciting parts of a text are the same part for you. But for clarity’s sake, I encourage you to indicate “confused” or “excited” unless you specifically feel both about the sentence in question. “Excited” could also mean “annoyed”—disagreement with authors is very welcome here, as long as you explain your thinking.
  • By “as briefly as possible,” I mean that writing one sentence each for parts i and ii is sufficient. If it takes more words to explain your thinking, feel free to use them. A successful response here is specific, not lengthy.
  • Our Canvas page will include examples of effective responses, and we will periodically check in about how the format can better serve our in-class discussions.

…

Readings and assignments by week

Week 1: Introductions

  • January 15: No reading

Week 2: An automated future?

  • January 20: No class
  • January 22: (Read in either order)
    • Astra Taylor, “The Automation Charade,” Logic(s) Magazine, August 2018.
    • James Somers, “A Coder Considers the Waning Days of the Craft,” The New Yorker, November 2023.

Week 3: The automated past

  • January 27: Chapter 2, “The Luddites: Diablo ex Machina,” in Keith Grint and Steve Woolgar, The Machine at Work: Technology, Work, and Organization (Polity Press ; Published in the USA by Blackwell, 1997).
  • January 29: Lucy Suchman, “The Uncontroversial ‘Thingness’ of AI,” Big Data & Society 10, no. 2 (2023), https://doi.org/10.1177/20539517231206794.
    • Optional: Elizabeth Stephens, “The Mechanical Turk: A Short History of ‘Artificial Artificial Intelligence’,” Cultural Studies 37, no. 1 (2023): 65–87, https://doi.org/10.1080/09502386.2022.2042580.

Week 4: At home

  • February 3: Introduction and Chapter 7 in Ruth Schwartz Cowan, More Work for Mother: The Ironies of Household Technology from the Open Hearth to the Microwave (Basic Books, 1983).
  • February 5: “Framing Fashion: Human-Machine Learning and the Amazon Echo Look” by Heather A. Horst and Sheba Mohammid in Sarah Pink et al., eds., Everyday Automation: Experiencing and Anticipating Emerging Technologies (Routledge, 2022), https://doi.org/10.4324/9781003170884.

Week 5: At the wheel

  • February 10: Chapter 1 (pages 15–38) in Jason Resnikoff, Labor’s End: How the Promise of Automation Degraded Work (University of Illinois Press, 2022).
    • Optional: David A. Hounshell, “Planning and Executing ’Automation’ at Ford Motor Company, 1945-65: The Cleveland Engine Plant and Its Consequences,” in Fordism Transformed: The Development of Production Methods in the Automobile Industry, ed. Haruhito Shiomi and Kazuo Wada (Oxford University Press, 1995).
  • February 12: Karen E. C. Levy, “The Contexts of Control: Information, Power, and Truck-Driving Work,” The Information Society 31, no. 2 (2015): 160–74, https://doi.org/10.1080/01972243.2015.998105.

Week 6: On the line

  • February 17: No class
  • February 19: Venus Green, “Race and Technology: African American Women in the Bell System, 1945-1980,” Technology and Culture 36, no. 2 (1995): S101–44, https://doi.org/10.2307/3106692.
  • February 20:

Week 7: In the factory

  • February 24: Chapter 5 (pages 77–105) in David F. Noble, Forces of Production: A Social History of Industrial Automation (Oxford University Press, 1984).
  • February 26: Chapter 8 (pages 189–204) in Rachel Plotnick, Power Button: A History of Pleasure, Panic, and the Politics of Pushing (The MIT Press, 2018).

Week 8: In the studio

  • March 3: Fred Turner, “Romantic Automatism: Art, Technology, and Collaborative Labor in Cold War America,” Journal of Visual Culture 7, no. 1 (2008): 5–26.
  • March 5: Jonathan Sterne and Elena Razlogova, “Machine Learning in Context, or Learning from LANDR: Artificial Intelligence and the Platformization of Music Mastering,” Social Media + Society 5, no. 2 (2019): 1–18, https://doi.org/10.1177/2056305119847525.
    • Optional: Harry H. Jiang et al., “AI Art and Its Impact on Artists,” Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society (Montreal QC Canada), ACM, August 2023, 363–74, https://doi.org/10.1145/3600211.3604681.

Week 9: In the office

  • March 10: Jessa Lingel and Kate Crawford, “Alexa, Tell Me about Your Mother”: The History of the Secretary and the End of Secrecy,” Catalyst: Feminism, Theory, Technoscience 6, no. 1 (2020), https://doi.org/10.28968/cftt.v6i1.29949.
  • March 12: Chapter 3, “Automated Hiring and Discrimination,” in Ifeoma Ajunwa, The Quantified Worker: Law and Technology in the Modern Workplace (Cambridge University Press, 2023), https://doi.org/10.1017/9781316888681.

Spring recess!

Week 10: Zooming out

  • March 24: Salem Elzway and Jason Resnikoff, “Whence Automation? The History (and Possible Futures) of a Concept,” Labor 21, no. 1 (2024): 27–41, https://doi.org/10.1215/15476715-10948907.
  • March 26: Langdon Winner, “Do Artifacts Have Politics?” Daedalus 109, no. 1 (1980): 121–36.

Week 11: Going off script

  • March 31: Project part 1 due – presentations in class
  • April 2: Madeleine Akrich, “The De-Scription of Technical Objects,” in Shaping Technology / Building Society: Studies in Sociotechnical Change, ed. Wiebe E. Bijker and John Law (MIT Press, 1992).

Week 12: Pushing back

  • April 7: Evan Calder Williams, “Manual Override,” in The New Inquiry, 2016.
    • Optional: Charles Denby, Workers Battle Automation (News & Letters, 1960).
  • April 9: Jamie Woodcock, “Towards a Digital Workerism: Workers’ Inquiry, Methods, and Technologies,” NanoEthics 15, no. 1 (2021): 87–98, https://doi.org/10.1007/s11569-021-00384-w.

Week 13: Automation, once and future

  • April 14: Chapters 2–4 in James Boggs, The American Revolution: Pages from a Negro Worker’s Notebook (Monthly Review, 1963).
  • April 16: Nyalleng Moorosi et al., “AI for Whom? Shedding Critical Light on AI for Social Good,” NeurIPS Computational Sustainability Workshop, 2023.

Week 14: Which way?

  • April 21: No class
  • April 23: Chapters 6 and 7 in Dan McQuillan, Resisting AI: An Anti-fascist Approach to Artificial Intelligence (Bristol University Press, 2022).

Week 15:

  • April 28: No reading

May 2: Project part 2 due