AI + Ethics: Creating Affinity and Race-Based Lesson Plans

Problem

Building on the previous AI Mentor Platform project, I am continuing to test for AI's intersection and understanding of race and critical education. My goal within these projects is to rigorously examine AI's capacity to have social justice sensibility when it comes to education. In this section, I developed a lesson prompt instructing how AI would deliver effective and meaningful curriculum that builds upon critical topics within the Asian American experience.

Learn more about what was behind the inspiration to test AI and its interaction with ideas of race and identity here.

Process

Progressing from testing AI's strength-based feedback in the previous, I wanted to see how Forefront.ai would respond when it is asked to edit an Asian American Affinity Toolkit for High School Students.

My curriculum included a check in, an identity mapping activity, and in depth closing prompt questions that were aimed to challenge conceptions about race. I developed an existing and thorough prompt for Forefront.ai to edit and refine:

"Act like an educator who is passionate about social justice and uplifting the Asian American experience. As a facilitator for an Asian American Affinity group, your role is to guide students in reflecting on their race and identity. Introduce yourself and emphasize your coaching role in this reflective process. Follow these steps below to design a lesson plan that is culturally inclusive and meaningful. Make sure the lesson plan is about 1 hour long. Here are some things to consider including:

  1. Presentation & Historical Context

    A. Begin the meeting by providing a brief historical overview of the Chinese Exclusion Act (1882) and its significance in Asian American history.

    B. Share primary sources like political cartoons, photographs, and documents related to the act to set the historical context.

  2. Lastly, include an identity mapping activity which ask students to "draw their identity map to illustrate their family's migration, or their own racial identity formation."

Results

Generative AI was able to do the following successfully:

  • Provide a structured framework and guide for teachers to follow

  • Giving introductions

  • Explaining why race and identity are important, and specifically how these activities aid the development of such critical topics

Constraints


Generative AI was not able to do the following:

  • Develop specificity and individualization. For example, AI used very generic social justice language and could not dig deeper into the foundational understandings of why this affinity toolkit lesson plan was so important, especially in todays context of racism in America.

  • Speak about the Chinese Exclusion Act in its full capacity and context. AI was only able to say it was a significant moment in history, but could not give any metrics or explanations. This may be a larger reflection of how algorithms about racist history is burried.

Questions to consider for next time:

  • How do we define race for generative AI models? Should we have jurisdiction over that?