Students will be responsible for submitting a question or a point of reflection (no more than a few sentences) each week to Canvas (starting Week 2, due by 5pm Thursdays). Questions should not be yes or no questions, but should help guide further discussion with your classmates. Reflections could include things that surprised you, challenged a prior view, confused you, failed to convince you, etc.
Mimi Onuoha’s art project “The Library of Missing Datasets” poses a provocative idea: what gets counted counts. In other words, the things that people choose to measure reflect what they value. In her project, she documents missing datasets: nobody has chosen to systematically measure gun trace data, or the cause of 2015 black church fires, etc.
Think of a dataset that doesn’t exist, and create it. This can be anything from measuring yourself with a Fitbit for a certain amount of time, or taking the temperature of a patch of grass outside your room for a week, to doing research on mass shootings or adding evidence to other national conversations. There is no requirement around the time-span for the dataset. E.g., “Dogs of Cambridge” takes a different approach to data collection vis-a-vis that of taking the temperature of a patch of grass outside your room for a week.
You will submit both the dataset and an approx. 500-word reflection on the process of creating it.
It’s the year 2050, 2070, or 2120. In the style of The New York Times series Op-Eds From the Future, write a 500-1200 word op-ed about a technology that has become pervasive in society and the risks and benefits associated with it. Example: https://www.nytimes.com/2019/11/04/opinion/future-scooters-central-park.html.
Google’s Teachable Machine is an online application that allows you to train a simple image-recognition AI without coding. Train three machine learning models using the following guidelines:
Write an approximately 500-word reflection on the process. Please upload your creative model using Teachable Machine and include the link in the reflection. The reflection can be open ended, but here are some example questions that can guide your thinking. What was interesting about the process of posing for data collection to act out different classes? What was interesting about choosing what the classes were, and what got left out? How does the classifier behave when the input doesn’t fit into any of the classes? What surprised you about the capabilities of the model you trained? What were its limitations?
Write a project proposal and an annotated bibliography of 8-10 sources toward a creative research project that shows significant understanding of an idea we’ve explored in the course. You may work individually or collaborate (no more than 3 per group), but each person’s contributions should be made clear. We will provide an assessment rubric for the final project and meet with you to discuss your ideas. This project is intentionally flexible in approach, and more information will follow throughout the semester. Possible forms for the final project may include but are not limited to: a research paper; web-based interactive storytelling or visualization; a substantive piece of speculative fiction; a design of a speculative alternative to an extant AI system; an ethnographic or oral history project; an interview-style piece or podcast; a self-defined creative project that leverages your unique talents!