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Research Methodology for Operationalizing Diversity and Inclusion Requirements for AI Systems

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Explore a detailed research methodology for implementing diversity and inclusion in AI, from data collection to user story templates and focus groups.

Authors: Muneera Bano; Didar Zowghi; Vincenzo Gervasi; Rifat Shams. Table of Links Abstract, Impact Statement, and Introduction Defining Diversity and Inclusion in AI Research Motivation Research Methodology Results Discussion Conclusion and Future Work and References IV.

Table of Links Abstract, Impact Statement, and Introduction Abstract, Impact Statement, and Introduction Defining Diversity and Inclusion in AI Defining Diversity and Inclusion in AI Research Motivation Research Motivation Research Methodology Research Methodology Results Results Discussion Discussion Conclusion and Future Work and References Conclusion and Future Work and References IV.

 

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AI for All: Operationalizing Diversity and Inclusion Requirements for AI SystemsExplore the importance of incorporating diversity and inclusion principles in AI system development through tailored requirements engineering.
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