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The expanding capabilities of operations research (OR) tools, fueled by massive data availability and machine learning, necessitate greater attention to their ethical implications. These dimensions include assessing societal impacts, engagement with prevailing values, and transparency in application. Current OR education often treats these tools as morally neutral, focusing on techniques without addressing the ethical responsibility of their use. This approach is increasingly problematic as mathematical tools significantly influence decision-making. Key ethical questions arise: Do analyses consider all affected parties, including non-human and environmental concerns? Are tools used transparently and critically, acknowledging limitations in uncertainty and risk modeling? Additionally, the societal consequences of narrowly rational perspectives, which may marginalize broader human purposes, demand scrutiny. Specific concerns include the potential loss of critical context through mathematization, the risks of narrowly focused optimization over time, and the assumption that all objectives are tradeable. These issues call for integrating ethical considerations into OR education and practice to balance efficiency with broader societal well-being and ensure responsible tool deployment.