AI doesn’t just reflect society—it amplifies its contradictions. From viral “bikini” image manipulation trends(!) in generative tools to hiring systems that systematically disadvantage women* in tech, we see the same pattern: erasure in one place, hypervisibility in another. In this hands-on workshop, we build AI agents with LangChain and LangGraph to detect and surface gender bias in real text systems—turning critique into code, and visibility into a technical feature.
We start by examining real-world examples of bias in tech and AI outputs, then move directly into building AI agents using LangChain and LangGraph. Participants will design and implement a pipeline that detects gender bias in text, classifies its severity, and generates more inclusive rewrites.
The focus is practical: turning bias from an abstract concept into something observable, measurable, and actionable through working AI agents.
AI Agents, Women* in Tech, Gender Bias, LangChain/LangGraph, LLMs