Overview
This practical guide shows, step by step, how to use machine learning to carry out actionable decisions that do not discriminate based on numerous human factors, including ethnicity and gender. The authors examine the many kinds of bias that occur in the field today and provide mitigation strategies that are ready to deploy across a wide range of technologies, applications, and industries.
Edited by engineering and computing experts, Mitigating Bias in Machine Learning includes contributions from recognized scholars and professionals working across different artificial intelligence sectors. Each chapter addresses a different topic and real-world case studies are featured throughout that highlight discriminatory machine learning practices and clearly show how they were reduced.
Mitigating Bias in Machine Learning addresses:
- Ethical and Societal Implications of Machine Learning
- Social Media and Health Information Dissemination
- Comparative Case Study of Fairness Toolkits
- Bias Mitigation in Hate Speech Detection
- Unintended Systematic Biases in Natural Language Processing
- Combating Bias in Large Language Models
- Recognizing Bias in Medical Machine Learning and AI Models
- Machine Learning Bias in Healthcare
- Achieving Systemic Equity in Socioecological Systems
- Community Engagement for Machine Learning
While major retailers like Amazon may carry Mitigating Bias in Machine Learning, we specialize in bulk book sales and offer personalized service from our friendly, book-smart team based in Portland, Oregon. We’re proud to offer a Price Match Guarantee and a streamlined ordering experience from people who truly care.
We’re trusted by over 75,000 customers, many of whom return time and again. Want proof? Just check out our 25,000+ customer reviews—real feedback from people who love how we do business.
Prefer to talk to a real person? Our Book Specialists are here Monday–Friday, 8 a.m. to 5 p.m. PST and ready to help with your bulk order of Mitigating Bias in Machine Learning.