Fr. 56.90

The Bridgerton Paradox in Artificial Intelligence - Balancing Diversity, Authenticity, and Responsible Innovation

Inglese · Copertina rigida

Spedizione di solito entro 6 a 7 settimane

Descrizione

Ulteriori informazioni

The term 'Bridgerton Paradox' is inspired by the Netflix series 'Bridgerton', which depicts a racially inclusive elite society in Regency-era England, challenging traditional historical accuracy in favor of modern tastes and sensibilities. This creative choice mirrors the broader ethical and methodological challenges faced by AI technologies, which must navigate the delicate interplay between contemporary values of diversity and the preservation of historical contexts. This book offers a critical and forward-thinking examination of the interplay between diversity and historical authenticity in AI within the organisational setting. It provides a robust theoretical foundation, practical guidelines, and real-world examples, guiding the development of AI strategies that are both innovative and ethically sound. It will be of great interest to scholars and students of AI in business and society, diversity and inclusion and innovation strategy, as well as practitioners and policymakers seeking a nuanced opinion on the interplay of diversity and AI technologies.

Sommario

Chapter 1: Introduction to the Bridgerton Paradox.- Chapter 2: Historical Context and Philosophical Foundations.- Chapter 3: Beyond the Buzzwords Confronting the Myths and Realities of Diversity in AI.- Chapter 4: The Role of Data: Representation and Bias.- Chapter 5: Balancing Historical Authenticity and Modern Inclusivity.- Chapter 6: Ethical Frameworks for AI Development.- Chapter 7: The SocioTechnical Systems Perspective.- Chapter 8: Toward a Decolonized AI.- Chapter 9: Memory Machines and the Futures We Inherit.

Info autore

Somendra Narayan
 is an Assistant Professor of Strategy and Innovation at the Amsterdam Business School, University of Amsterdam, The Netherlands, and the Director of the Amsterdam Digital Transformation Lab. His research focuses on strategic change in the context of emerging technologies, particularly artificial intelligence, with an emphasis on purposeful and sustainable business model innovation, strategic decision-making under complexity, and the role of cognitive diversity, decolonial thought, and pluralist epistemologies in fostering inclusive innovation. His work further engages with themes like responsible digital transformation, quantum transformations, digital social entrepreneurship, and green-digital twin transitions from a socio-technical systems perspective.

Riassunto

The term 'Bridgerton Paradox' is inspired by the Netflix series 'Bridgerton', which depicts a racially inclusive elite society in Regency-era England, challenging traditional historical accuracy in favor of modern tastes and sensibilities. This creative choice mirrors the broader ethical and methodological challenges faced by AI technologies, which must navigate the delicate interplay between contemporary values of diversity and the preservation of historical contexts. This book offers a critical and forward-thinking examination of the interplay between diversity and historical authenticity in AI within the organisational setting. It provides a robust theoretical foundation, practical guidelines, and real-world examples, guiding the development of AI strategies that are both innovative and ethically sound. It will be of great interest to scholars and students of AI in business and society, diversity and inclusion and innovation strategy, as well as practitioners and policymakers seeking a nuanced opinion on the interplay of diversity and AI technologies.

Dettagli sul prodotto

Autori Somendra Narayan
Editore Springer, Berlin
 
Lingue Inglese
Formato Copertina rigida
Pubblicazione 07.10.2025
 
EAN 9783031994920
ISBN 978-3-0-3199492-0
Pagine 105
Illustrazioni XIX, 105 p. 9 illus.
Categorie Scienze sociali, diritto, economia > Economia > Management

Künstliche Intelligenz, Personalmanagement, HRM, Artificial Intelligence, Postmodernism, Business Ethics, Biases, Diversity Management and Women in Business, Innovation and Technology Management, inclusivity, Datasets, AI-generated content

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