
ISBN13: | 9781032074443 |
ISBN10: | 1032074442 |
Binding: | Hardback |
No. of pages: | 130 pages |
Size: | 198x129 mm |
Weight: | 140 g |
Language: | English |
Illustrations: | 10 Illustrations, black & white; 8 Halftones, black & white; 2 Line drawings, black & white |
491 |
Natural sciences in general, history of science, philosophy of science
Number theory
Electrical engineering and telecommunications, precision engineering
Energy industry
Theory of computing, computing in general
System organization
Operating systems and graphical user interfaces
Computer programming in general
Software development
Artificial Intelligence
Safety and health aspects of computing
Man-machine interaction
Environmental sciences
AI for Diversity
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AI for Diversity questions how AI technology can lead to inclusion or exclusion for diverse groups of society. It enables the reader to step back and see how AI is impacting diversity in humans impacted by AI and how diversity-awareness strategies can impact AI.
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.
"The book is written in a really approachable way for non-specialists and will engage introductory and interdisciplinary audiences. The sections on gender and queering AI are particularly strong, and the book is a highly worthy and important contribution for those chapters alone." --Ashley Shew, Associate Professor, Virginia Tech
1.Opening the Black Box of AI. 2. Gendered AI: performativity, expectations, and sexism. 3. Queering AI: gender expression, identity, and binaries. 4. AI and Race: recognition, bias, and systemic issues. 5. Bodies and AI: Health, ageing, and disabilities. 6. AI and Class: socioeconomic issues reproduced by technology. 7. Intersectionality and Responsible AI.