AI优化工具需超越公平性，全流程关注伦理问题。
Beyond Algorithmic Fairness: A Guide to Develop and Deploy Ethical AI-Enabled Decision-Support Tools
- 从建模到部署，全程嵌入伦理考量。
- 以电力与供应链案例揭示伦理风险。
- 推动研究者反思决策各环节的道德影响。
人工智能与优化的融合在提升工程系统效率、可靠性和韧性方面具有巨大潜力。由于许多工程系统具有网络化特征，将此类方法在该交叉领域进行伦理化部署面临独特挑战，因此需要制定针对AI增强型优化的专门伦理指南。本文强调应超越仅关注公平性的算法设计，系统性地涵盖建模、数据整理、结果分析及优化决策支持工具实施等各阶段的伦理问题。通过电力系统以及供应链与物流领域的案例研究，识别出在人工智能与优化交汇处部署算法所需的伦理考量。本文不提供具体规则，而是旨在促进研究人员的反思与意识觉醒，鼓励在决策过程的每个步骤中充分考虑伦理影响。
原文摘要 · Abstract (English)
The integration of artificial intelligence (AI) and optimization hold substantial promise for improving the efficiency, reliability, and resilience of engineered systems. Due to the networked nature of many engineered systems, ethically deploying methodologies at this intersection poses challenges that are distinct from other AI settings, thus motivating the development of ethical guidelines tailored to AI-enabled optimization. This paper highlights the need to go beyond fairness-driven algorithms to systematically address ethical decisions spanning the stages of modeling, data curation, results analysis, and implementation of optimization-based decision support tools. Accordingly, this paper identifies ethical considerations required when deploying algorithms at the intersection of AI and optimization via case studies in power systems as well as supply chain and logistics. Rather than providing a prescriptive set of rules, this paper aims to foster reflection and awareness among researchers and encourage consideration of ethical implications at every step of the decision-making process.
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