Beyond Algorithmic Fairness: A Guide to Develop and Deploy Ethical AI-Enabled Decision-Support Tools

The integration of artificial intelligence (AI) and optimization is transforming the landscape of engineered systems, offering unprecedented opportunities to enhance efficiency, reliability, and resilience across domains (Palle, 2023) such as power systems (Thirunavukkarasu et al., 2023), supply chains, and logistics (Joel et al., 2024). As these networked systems become more dependent on AI-enabled decision support tools, the ethical challenges associated with their deployment grow more complex (Whittlestone and Clarke, 2022). Traditional ethical concerns in AI--such as fairness, accountability, and transparency--take on new dimensions when applied to systems characterized by complex networks and optimization processes, where decisions have far-reaching societal impacts (Jobin et al., 2019). Governments and organizations worldwide have responded to these ethical concerns by introducing frameworks and regulations aimed at ensuring trustworthy AI (Harrison and Luna-Reyes, 2022; Weaver, 2021; Aoki et al., 2024; Madhavan et al., 2020). Initiatives like the European Union's AI Act (Parliament and of the European Union, 2024) and the Biden-Harris administration's AI Bill of Rights (Biden, 2021) aim to safeguard fairness, transparency, and accountability in AI systems (White House Office of Science and Technology Policy, 2023; OECD, 2020; Radu, 2021).