Open Educational Resources
Document Type
Assignment
Publication Date
Fall 12-30-2025
Abstract
This assignment examines bias and stereotyping in AI image generation systems while teaching students the conventions of scientific genre writing through a formal lab report. Working in interdisciplinary groups, students generate image datasets using gender-neutral professional terms and analyze representations of gender, race, and age. Findings are compared with real-world labor demographics to assess discrepancies between AI outputs and existing data. Students practice core lab report conventions, including hypothesis formation, methods documentation, results presentation, and discussion, while integrating analysis and scholarly research. By combining empirical investigation with structured academic writing, the assignment strengthens students’ ability to communicate complex findings clearly within the lab report genre.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.
CUNY OER Funding
CUNY OER Initiative
