TRUTH, RISK, AND RESPONSIBILITY

A CRITICAL SYNTHETIC REALIST ETHICAL REASSESSMENT OF THE NIST ARTIFICIAL INTELLIGENCE RISK MANAGEMENT FRAMEWORK

Abstract

As artificial intelligence (AI) systems increasingly mediate high-stakes decisions in healthcare, finance, governance, security, and education, ethical concerns have intensified beyond technical performance to questions of legitimacy, responsibility, and truth. In response, the U.S. National Institute of Standards and Technology (NIST) introduced the Artificial Intelligence Risk Management Framework (AI RMF) as a voluntary, lifecycle-oriented guide for managing AI-related risks (NIST, 2023). While the framework represents a significant operational advance, this paper argues that its ethical adequacy depends on deeper philosophical commitments that remain under-theorized.

Drawing on Critical Synthetic Realism (CSR), this study offers a normative ethical reassessment of the NIST AI RMF. CSR integrates ontological realism, epistemic fallibilism, and moral responsibility, enabling a critique that moves beyond instrumental risk mitigation toward truth-centered governance. The analysis contends that ethical AI governance must be grounded not only in probabilistic risk management but also in epistemic integrity, moral realism, and institutional accountability for algorithmic truth-claims. Without such grounding, risk-based frameworks risk legitimizing harmful systems through procedural compliance rather than moral justification.

The paper concludes by proposing normative enhancements to the AI RMF that integrate truth-based ethics, enforceable accountability, and human-centered governance. These enhancements aim to bridge the gap between technical risk management and moral responsibility in algorithmically mediated societies.