Towards a Standard for Identifying and Managing Bias in Artificial Intelligence

By Reva Schwartz et al

Published on March 10, 2022

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Table of Contents

Executive Summary
1. Purpose and Scope
2. AI Bias: Context and Terminology
3. AI Bias: Challenges and Guidance
4. Conclusions
5. Glossary

Summary

This document addresses the challenges of bias in artificial intelligence (AI) and provides guidance for identifying and managing bias in AI systems. It discusses the impact of biases on public trust, categorizes AI bias into systemic, statistical, and human factors, and outlines challenges and guidance for mitigating bias in datasets, testing and evaluation, and human factors. The document emphasizes the importance of a socio-technical perspective in addressing AI bias and aims to provide a roadmap for developing detailed guidance on managing bias in AI systems.