构建253个问题库，系统评估AI的包容性水平。
A Question Bank to Assess AI Inclusivity: Mapping out the Journey from Diversity Errors to Inclusion Excellence
- 设计5大维度253个问题，覆盖人、数据、流程等环节。
- 通过70个模拟角色验证，问题库能有效识别包容性短板。
- 适合研究者、开发者和政策制定者用于提升AI公平性。
确保人工智能中的多样性与包容性（D&I）对于减少偏见、促进公平决策至关重要。然而，现有AI风险评估框架常忽视包容性，缺乏标准化工具来衡量AI系统对D&I原则的契合度。本文提出一个结构化的AI包容性问题库，包含253个问题，涵盖人类、数据、流程、系统和治理五大支柱。该问题库通过多源迭代方法开发，综合文献综述、D&I指南、负责任AI框架及一次模拟用户研究。以70个与不同AI岗位相关的生成型人物进行模拟评估，检验其在多样化角色和应用场景下的相关性与有效性。结果强调将D&I原则融入AI开发流程与治理结构的重要性。该问题库为研究人员、实践者和政策制定者提供可操作工具，助力系统性评估并提升AI系统的包容性，推动更公平、负责任的人工智能发展。
原文摘要 · Abstract (English)
Ensuring diversity and inclusion (D&I) in artificial intelligence (AI) is crucial for mitigating biases and promoting equitable decision-making. However, existing AI risk assessment frameworks often overlook inclusivity, lacking standardized tools to measure an AI system's alignment with D&I principles. This paper introduces a structured AI inclusivity question bank, a comprehensive set of 253 questions designed to evaluate AI inclusivity across five pillars: Humans, Data, Process, System, and Governance. The development of the question bank involved an iterative, multi-source approach, incorporating insights from literature reviews, D&I guidelines, Responsible AI frameworks, and a simulated user study. The simulated evaluation, conducted with 70 AI-generated personas related to different AI jobs, assessed the question bank's relevance and effectiveness for AI inclusivity across diverse roles and application domains. The findings highlight the importance of integrating D&I principles into AI development workflows and governance structures. The question bank provides an actionable tool for researchers, practitioners, and policymakers to systematically assess and enhance the inclusivity of AI systems, paving the way for more equitable and responsible AI technologies.
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