How do algorithms reflect bias in everyday search results?

Originally published on January 8, 2026

This lesson is part of a broader set of AI Auditing for High School materials developed by UPenn GSE. CRAFT provides this page as a curated entry point, linking educators directly to the original lesson resources for classroom use.

Overview

Search engines and other AI systems shape how people see the world, often in ways that feel neutral or objective. However, these systems can reflect and amplify social biases that are embedded in data, design choices, and societal patterns. In this lesson, students investigate algorithmic bias through image search results, using everyday search terms to uncover patterns related to race, gender, and representation. Through discussion, annotation, and reflection, students develop a sense of agency by learning how everyday people can question, audit, and respond to biased algorithmic systems.

AI & Society
60 minutes

Originally developed by the University of Pennsylvania Graduate School of Education as part of the AI Auditing for High School (beta) curriculum

Digital Materials

Teacher guide

Objectives

By the end of this lesson, students will be able to:

Draw on their prior experiences with AI systems they use in daily life
Investigate patterns and biases in image search results
Identify how algorithmic bias appears in real-world technologies
Reflect on the emotional and social impacts of biased algorithmic representations

Questions explored

What kinds of patterns appear in image search results for common occupations or roles?
How can bias show up in AI systems, even without harmful intent?
Why do representation and visibility matter in algorithmic outputs?
Where do everyday people have power or agency in systems affected by algorithmic bias?

Key Terms

Algorithmic Bias

When AI produces repeatable errors that create unfair outcomes, favoring some groups over others.

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