AI for Diversity
- Length: 118 pages
- Edition: 1
- Language: English
- Publisher: CRC Press
- Publication Date: 2023-01-27
- ISBN-10: 103207356X
- ISBN-13: 9781032073569
- Sales Rank: #0 (See Top 100 Books)
Artificial intelligence (AI) is increasingly impacting many aspects of people’s lives across the globe, from relatively mundane technology to more advanced digital systems that can make their own decisions. While AI has great potential, it also holds great peril depending on how it is designed and used. AI for Diversity questions how AI technology can lead to inclusion or exclusion for diverse groups in society. The way data is selected, trained, used, and embedded into societies can have unfortunate consequences unless we critically investigate the dangers of systems left unchecked, and can lead to misogynistic, homophobic, racist, ageist, transphobic, or ableist outcomes. This book encourages the reader to take a step back to see how AI is impacting diverse groups of people and how diversity-awareness strategies can impact AI.
Cover Half Title Series Page Title Page Copyright Page Table of Contents Preface Who is this Book not for? Acknowledgments Abbreviation List Chapter 1: Opening the Black Box of AI What Is AI? AI Machine Learning in Practice What Is Diversity? Why AI for Diversity—A Socio-Technical Approach Societal Implications of AI Bias Summary References Chapter 2: Gendered AI: Performativity, Expectations, and Sexism Vantage Points for Understanding Gender AI’s Understanding of Gender Sexist AIs? Robots and Gender AI and Sex Summary References Chapter 3: Queering AI: Gender Expression, Identity, and Binaries AI’s Potential for Discrimination Predicting Gender and Sexuality Categorizing and Exclusion Summary References Chapter 4: AI and Race: Recognition, Bias, and Systemic Issues AI’s Phrenological Turn Facial Recognition Bias Bias in Law Enforcement Systems AI Is Not Color Blind Summary References Chapter 5: Bodies and AI: Health, Aging, and Disabilities Artificial Health or Intelligent Health? (Re)defining the ‘Elderly’ Sensory Monitoring Caring from a Distance Mental Health Issues COVID, AI, and Healthcare Diversity AI and Disabilities Death with AI—Heaven Is a Place on Earth? Summary Note References Chapter 6: AI and Class: Work, Education, and Sustainability Computer Says No-Money, No-Go Top-Down Control in the Workplace Class-Based Access to Education (Un)sustainable AI East Asian AI AI in Africa Summary References Chapter 7: Intersectionality and Responsible AI Intersectional Issues with AI Toward Sociotechnical Diversity in AI? Pathways Toward Responsible AI? Further Resources Summary References Index
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