This is the home page of the course syllabus, which outlines all the instructions, logistics, and expectations for the course. The syllabus also has a schedule page, which details the reading and activities for each session. Make sure you are ENTIRELY familiar with these two pages.
How do we know what we know—and what happens when machines start “knowing” things too? (and: do they?)
This course uses historical practices and narratives as a laboratory for exploring how AI can sharpen critical thinking, deepen research, and produce higher-quality intellectual work. Rather than treating AI as a shortcut or a threat, we treat it as a thinking partner: a tool that, when used deliberately, makes visible our own reasoning processes and exposes the assumptions we bring to interpretation, evidence, and argument.
Students will practice making sense of the past with the help of AI. The question we explore: how can it actually be helpful, as opposed to just stringing together words that sounds authoritative. Some activities: finding sources, evaluating trustworthiness, synthesizing evidence, constructing arguments, identifying omissions. We constantly work alongside AI, learning when it helps, when it misleads, and what the difference reveals about how knowledge and expertise actually works.
How can AI help us think more critically, develop skills, and produce higher-quality work than we could without it?
All readings are available online or through Zotero. You never need to find anything!
The class builds toward a collaborative website that tells a public-facing story about the history of learning technologies and how they changed what it meant to “know” something—from medieval manuscript culture through the printing press, encyclopedias, libraries, the internet, and now AI.
Each student researches one historical moment or technology, using AI as a research partner throughout, and contributes to the collective site. This theme lets the class constantly mirror its own process: you are learning with AI while documenting the history of learning with tools.
You get graded on effort on this class, and the way you show effort is to show your work. It’s like math class, but without the math. I only care about the energy you put into an assignment, not what the final product is. It’s the process that’s important.
| Percent | Grade |
|---|---|
| 98+ | A+ |
| 92-97 | A |
| 90-91 | A- |
| 87-89 | B+ |
| 82-86 | B |
| 80-81 | B- |
| 77-79 | C+ |
| 73-76 | C |
| 70-72 | C- |
| 66-69 | D+ |
| 60-65 | D |
| 59- | F |
For almost everything we read, we’re reading to ENGAGE with it, not because it’s right. There is a LOT to disagree with across the readings, and we don’t all have to agree on everything. The goal is to develop frameworks for thinking critically about AI, knowledge, and expertise.
If life gets overwhelming during the course, please reach out. We can discuss accommodations, deadline adjustments, or other support. The goal is maximizing learning under real life circumstances, not draconian rule-following.