Human factors in the standardization of AI governance: Improving the design of risk management standards for ethical AI

The field of AI governance is rapidly standardizing, with notable examples such as the NIST AI Risk Management Framework (AI RMF) and ISO/IEC 42001 illustrating a standardized risk management approach. However, a significant disconnect persists between academic research and practitioner needs, with the latter relying on industry standards for real-world implementation of ethical principles. These emerging standards, while promising, remain untested and face numerous challenges in effectively governing the complex and dynamic field of AI. This dissertation examines the standardization of AI governance, adopting a constrained optimization approach to improve AI standards. The research addresses three key questions: (1) What are the system-level requirements for standardization as a governance framework for human-centered AI systems? (2) What are the unit-level requirements for standards as a governance instrument for human-centered AI systems? (3) How can AI Risk Standards be designed to achieve better outcomes in the development of human-centered AI systems? Through three empirical contributions, this work aims to enhance emerging AI standards by focusing on the standards themselves, the AI practitioners who will implement them, and the organizational contexts in which they operate. The research provides practical guidance for AI practitioners tasked with implementing AI standards and offers recommendations for standard developing organizations. By addressing the challenges of AI governance through standardization, this dissertation contributes to the development of more effective, human-centered AI systems. It bridges the gap between theoretical principles and practical implementation, offering insights that can shape the future of AI governance and ensure the responsible development of AI technologies.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Information Sciences

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Kilhoffer, Zachary

Contributors dc:contributor

• Sanfilippo, Madelyn
• Wang, Yang
• Bashir, Masooda
• Ma, Jiaqi

• AI Governance
• Trustworthy AI
• Ethical AI
• AI Standards

Statement dc:rights

• Copyright 2025 Zachary Kilhoffer

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129214

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129214