The growing presence of Artificial Intelligence (AI) in various sectors
necessitates systems that accurately reflect societal diversity. This study
seeks to envision the operationalization of the ethical imperatives of
diversity and inclusion (D&I) within AI ecosystems, addressing the current
disconnect between ethical guidelines and their practical implementation. A
significant challenge in AI development is the effective operationalization of
D&I principles, which is critical to prevent the reinforcement of existing
biases and ensure equity across AI applications. This paper proposes a vision
of a framework for developing a tool utilizing persona-based simulation by
Generative AI (GenAI). The approach aims to facilitate the representation of
the needs of diverse users in the requirements analysis process for AI
software. The proposed framework is expected to lead to a comprehensive persona
repository with diverse attributes that inform the development process with
detailed user narratives. This research contributes to the development of an
inclusive AI paradigm that ensures future technological advances are designed
with a commitment to the diverse fabric of humanity.

本研究提出了一种利用生成人工智能 (GenAI) 进行基于角色的模拟的工具的框架愿景，旨在促进需求分析过程中对多样化用户需求的表示，从而为人工智能软件的开发过程提供详细的用户叙述，以发展一种包容性的人工智能范式，确保未来的技术进步符合多样人类群体的需求。

AI 中多样性和包容的运营愿景

A Vision for Operationalising Diversity and Inclusion in AI

As Artificial Intelligence (AI) permeates many aspects of society, it brings
numerous advantages while at the same time raising ethical concerns and
potential risks, such as perpetuating inequalities through biased or
discriminatory decision-making. To develop AI systems that cater for the needs
of diverse users and uphold ethical values, it is essential to consider and
integrate diversity and inclusion (D&I) principles throughout AI development
and deployment. Requirements engineering (RE) is a fundamental process in
developing software systems by eliciting and specifying relevant needs from
diverse stakeholders. This research aims to address the lack of research and
practice on how to elicit and capture D&I requirements for AI systems. We have
conducted comprehensive data collection and synthesis from the literature
review to extract requirements themes related to D&I in AI. We have proposed a
tailored user story template to capture D&I requirements and conducted focus
group exercises to use the themes and user story template in writing D&I
requirements for two example AI systems. Additionally, we have investigated the
capability of our solution by generating synthetic D&I requirements captured in
user stories with the help of a Large Language Model.

开发人工智能系统应当考虑与整合多样性和包容性原则，本研究旨在解决如何获取和捕捉多样性和包容性需求对人工智能系统的不足进行综合数据搜集和综合分析。