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.
Author(s): Roger A. Søraa
Series: AI for Everything
Publisher: CRC Press
Year: 2022
Language: English
Pages: 130
City: Boca Raton
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
