Ozobot Classroom

Invisible Inputs: Analyzing Bias in AI Healthcare Tools

Students investigate how biased proxy data led a healthcare algorithm to underestimate the needs of certain patient groups. They analyze the case, debate fairness, and use Color Codes to model how design choices affect equity in AI.

Elective Algorithm Design

Students compare their own class scheduling decisions to those made by AI to identify possible bias in the AI algorithm. Then, they design ethical decision trees and use Ozobot Color Codes to model fair and equitable outcomes.

Ethics Lab: AI on Trial

Step into the role of an AI Ethicist! Students will investigate how AI can make biased decisions, propose improvements, and use Color Codes to demonstrate their evaluation of AI decisions with Ozobot.