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Artificial intelligence (AI) is rapidly transforming the world of work, but how does it impact diversity, equity, and inclusion (DEI)? AI and Diversity in a Datafied World of Work: Will the Future of Work be Inclusive? addresses the critical question of whether AI will create more inclusive workplaces or exacerbate existing inequalities. As AI systems become embedded in business practices, this work explores the potential for both harm and opportunity in how AI influences DEI efforts.
This collected edition delves into key areas such as AI's role in HR management, its impact on marginalised communities, and the risks of bias in algorithmic decision-making. Topics like job displacement, the inclusion of vulnerable workers, and the ethical challenges of AI in management are thoroughly explored, offering interdisciplinary insights from diverse academic perspectives and global contexts. The authors also present strategies to design AI systems that promote inclusion and fairness.
Designed for scholars, practitioners, and anyone interested in the intersection of technology and DEI, this work offers a rich examination of the challenges and opportunities AI presents for the future of work. Bridging theory with practice provides readers with the tools to navigate and shape the evolving landscape of AI in ways that foster inclusivity.
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Artificial intelligence (AI) is rapidly transforming the world of work, but how does it impact diversity, equity, and inclusion (DEI)? AI and Diversity in a Datafied World of Work: Will the Future of Work be Inclusive? addresses the critical question of whether AI will create more inclusive workplaces or exacerbate existing inequalities. As AI systems become embedded in business practices, this work explores the potential for both harm and opportunity in how AI influences DEI efforts.
This collected edition delves into key areas such as AI's role in HR management, its impact on marginalised communities, and the risks of bias in algorithmic decision-making. Topics like job displacement, the inclusion of vulnerable workers, and the ethical challenges of AI in management are thoroughly explored, offering interdisciplinary insights from diverse academic perspectives and global contexts. The authors also present strategies to design AI systems that promote inclusion and fairness.
Designed for scholars, practitioners, and anyone interested in the intersection of technology and DEI, this work offers a rich examination of the challenges and opportunities AI presents for the future of work. Bridging theory with practice provides readers with the tools to navigate and shape the evolving landscape of AI in ways that foster inclusivity.