International Journal on Science and Technology

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Responsible Automation: Ethical Implications of AI in Infrastructure Deployment and Procurement

Author(s) Soumya Remella
Country United States
Abstract Artificial intelligence (AI) is transforming how infrastructure projects are procured, managed, and executed. Algorithms now evaluate suppliers, forecast risks, and guide billion-dollar decisions once reserved for human experts. While these systems enhance efficiency, they also introduce ethical and governance challenges—bias, opacity, and diffusion of accountability—that can undermine public trust. This paper introduces the Responsible Automation Framework (RAF), a governance-oriented model designed to embed ethical oversight directly into automated decision systems used in infrastructure procurement. Built on four layers—Governance, Transparency, Accountability, and Sustainability—RAF operationalizes fairness and responsibility throughout the AI lifecycle. The framework was developed through a qualitative, conceptual methodology combining literature synthesis, policy analysis, and hypothetical case reasoning. A proposed pilot validation protocol and Ethical Audit Toolkit (EAT) further extend RAF’s practical application by offering measurable indicators and audit mechanisms. Through comparative analysis with existing standards such as the EU AI Act, ISO 37001, and IEEE EAD guidelines, RAF demonstrates superior adaptability and ethical resilience. The study concludes that embedding ethics structurally—rather than as a compliance afterthought—can enable trustworthy, transparent, and sustainable automation in public infrastructure governance.
Keywords Artificial Intelligence (AI); Responsible Automation; Ethical Governance; Infrastructure Procurement; Transparency; Accountability; Fairness; Sustainability; AI Ethics; Public Sector Automation; Responsible AI Framework.
Field Engineering
Published In Volume 16, Issue 4, October-December 2025
Published On 2025-10-23
DOI https://doi.org/10.71097/IJSAT.v16.i4.9555
Short DOI https://doi.org/hbb8f2
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