Async Online

July 2th-17th 2026

The first two weeks of this course are online. You’ll complete two assignments and engage with several readings during this period. We’ll use Slack as our primary mode of communication during this time.

Week 1 (July 2nd-10th): A starting place for GenAI: Introductions, Ideas, and Experimentation.

Description:  

This first week aims to immerse us in some core concepts and frames for thinking about AI and GenAI. While many of us likely have a passing familiarity with GenAI, the scholarship for this week seeks to trouble and introduce tensions for us to consider as it relates to what GenAI actually is (and is not), how it works, its processes and limitations, and its connections to sociocultural, economic, political, ecological, and educational systems. GenAI’s place in this chain of relationships has quickly become taken-for-granted, so it is vital that we peak under the hood (or inside the black-box, if you prefer) to really get a sense of what is going on behind the algorithm(s), synthetic machine(s), and LLMs (large-language model) etc. What, for example, is the cost of this explosion in growth in the last decade or so, in terms of raw materials, conflict minerals, energy consumption, and the leveraging of precarious and underpaid labour? How well do these tools ‘learn’ and work? This week is about finding our footing and getting introduced to some of the important research ongoing in this subject field. As part of this, students will spend some time experimenting with GenAI themselves and reflecting upon some of its blind spots and biases.  

Readings:

  1. Coleman, B. (2021). Technology of The Surround. Catalyst: Feminism, Theory, Technoscience, 7(2), 1–21. 
  2. Crawford, K. (2021). Atlas of AI: Power, Politics and the Planetary Costs of Artificial Intelligence. Yale University Press. 
  3. Hao, K. (2025). Empire of AI: Dreams and nightmares in Sam Altman’s OpenAI. Penguin Press. Chapters 2, 12, 18. 

Viewing (Optional):

  • Roher, D., & Tyrell, C. (Directors). (2026). The AI Doc: Or How I Became an Apocaloptimist [Film]. Playgrounds; Cottage M; Fishbowl Films.
  • Veatch, V. (Director). (2026). Ghost in the Machine [Film]. Distributed Artificial Intelligence Research Institute (DAIR); PBS Documentaries; Kinema.  

Assignment: 

  • AI Bias and Blind Spots Simulation, DUE July 10th by 11:59pm PDT, submit via Slack 

Further reading (optional):

  • Buolamwini, J. (2023). Unmasking AI: My mission to protect what is human in a world of machines. Random House.  
  • Christian, B. (2020). The alignment problem: Machine learning and human values. W. W. Norton & Company.

Week 2 (July 10th-17th): Critically evaluating the place(s) and use(s) of GenAI in learning, teaching, and the workplace.

Description: 

In the second week, we seek to make connections between critical scholarship on AI/GenAI and some of the ways in which it might be reshaping information, knowledge, learning, work, play, and even love, as Winterson reveals for us. Once we have established a working understanding of what GenAI is, the question becomes what we are doing with it, and how these use cases are affecting personal, professional, and educational spaces. This brings us to more experimentation, this time taking the form of developing our own use case for GenAI, and our own framework (or heuristic) for evaluating its use in this setting. Can a GenAI tool help me write comments for student feedback? How would I evaluate its level of success on that task? Perhaps GenAI can sit in for me in a meeting at work? How could I evaluate if it catches the most important information? Questions like these are what you are invited to pose and explore with this week’s assignment. Perhaps a final note of caution though, for all hype and bombast that surrounds AI/GenAI in our present moment, Suchman reminds us that one of the great successes of AI has been its capacity to render itself as mundane and innocuous, just one more (ubiquitous) ‘thing’ we can collectively shrug at as we ignore the first few results of our google search, or ask chatGPT to check our work for grammar and clarity.

Readings:  

  1. Suchman, L. (2023). The uncontroversial ‘thingness’ of AI. Big Data & Society, 10(2) https://doi.org/10.1177/20539517231206794 
  2. Bucher, T. (2025). Beyond the hype: Reframing AI through algorithms and culture. Journal of Communication, 75(1), 81-84. 
  3. Horvath, J. C. (2025). The digital delusion: How classroom technology harms our kids’ learning—and how to help them thrive again. LME Global. Chapters 6 & 7.
  4. Winterson, J. (2021). 12 Bytes: How Artificial Intelligence will change the way we live and love. Vintage. Chapters 1, 2, and 3. (**Note this book is alternatively titled “12 Bytes: How We Got Here. Where We Might Go Next.” in an more recent re-print) 

Viewing (Required): 

Assignment: 

  • Evaluation Heuristic and Testing, DUE July 17 by 11:59pm PDT, submit via Slack 

Further Reading: 

  • Baron, N. S. (2026). Reader bot: What happens when AI reads and why it matters. Stanford University Press.