NIST: Comments Received on Proposal for Identifying and Managing Bias in AI

government

NIST·nist.gov/artificial-intelligence/comments-received-propos...

Credibility Rating

5/5

Gold(5)

Gold standard. Rigorous peer review, high editorial standards, and strong institutional reputation.

Rating inherited from publication venue: NIST

This is a U.S. government regulatory document collecting public input on NIST SP 1270, relevant to researchers and practitioners working on AI fairness, bias mitigation standards, and AI governance frameworks.

Metadata

Importance: 42/100guidance documentprimary source

Summary

This NIST webpage compiles public stakeholder comments on the draft Special Publication 1270, which proposes frameworks for identifying and managing bias in AI systems. Commenters highlight concerns around accountability in decision-making, data representativeness, transparency, and ensuring AI outputs achieve intended outcomes without disproportionate harm to specific populations.

Key Points

•Stakeholders emphasize that accountability mechanisms—analogous to Sarbanes-Oxley for financial reporting—are essential for managing AI bias.
•Commenters stress that AI trustworthiness depends on training data that is genuinely representative across demographics such as gender, age, and race.
•Transparency in stakeholder engagement across domains is identified as critical to both accountability and rationale for AI decisions.
•Concerns raised that AI systems must be verified to achieve intended outcomes without creating zero-sum negative impacts on select populations.
•Public comment process reflects NIST's collaborative approach to developing bias management standards through broad stakeholder input.

Cited by 1 page

Page	Type	Quality
NIST and AI Safety	Organization	63.0

Cached Content Preview

HTTP 200Fetched Mar 15, 202698 KB

Comments Received on A Proposal for Identifying and Managing Bias in Artificial Intelligence (SP 1270) | NIST 
 
 
 
 

 

 
 
 
 Skip to main content
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 Official websites use .gov 
 

 A .gov website belongs to an official government organization in the United States.
 

 
 
 
 
 
 
 Secure .gov websites use HTTPS 
 

 A lock ( 
 
 Lock 
 A locked padlock 
 
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
 

 
 
 
 
 
 
 

 
 
 
 
 https://www.nist.gov/artificial-intelligence/comments-received-proposal-identifying-and-managing-bias-artificial

 
 

 

 
 
 
 
 

 

 

 
 
 
 

 
 

 

 
 
 
 
 
 
 
 
 Artificial intelligence 

 
 
 

 
 

 
 
 
 
 

 
 
 
 
 
 
 
 
 
 

 
 
 

 

 

 

 

 
 

 
 
 
 

 
 
 

 
 
 
 
 
 
 
 
 
 Comments Received on A Proposal for Identifying and Managing Bias in Artificial Intelligence (SP 1270)

 
 

 
 
 
 
 
 Share

 
 
 
 
 Facebook 
 
 
 
 
 Linkedin 
 
 
 
 
 X.com 
 
 
 
 
 Email 
 
 
 
 
 
 

 
 

 
 
 
 
 
 
 
 We are seeking your feedback on our recently released first draft document of “ A Proposal for Identifying and Managing Bias in Artificial Intelligence " (Special Publication 1270).

 

 
 
 
 
 Comment number 

 
 
 Commenter organization 

 
 
 Commenter name 

 
 
 Document line or section referenced (if available) 

 
 
 Comment 

 
 
 
 
 
 
 1

 
 
 President of The Foundation for Sustainable Communities & Sr. Adjunct Professor

 
 
 Deborah Hagar, MBA

 
 
 319

 
 
 A key link to identifying and establishing accountability for bias is in the decision making process - human interventions. The accountability link for results is the key. Ex. Sarbannes-Oaxley idientified responsibility.

 
 
 
 
 
 President of The Foundation for Sustainable Communities & Sr. Adjunct Professor

 
 
 Deborah Hagar, MBA

 
 
 397

 
 
 Ensuring the identification and full engagement across domains is critical to both accountability and rationale for proposed decisions (i.e., transparency)

 
 
 
 
 
 President of The Foundation for Sustainable Communities & Sr. Adjunct Professor

 
 
 Deborah Hagar, MBA

 
 
 410

 
 
 This is the key! The full cycle of implementation is the true test that the outputs result in the intended AND desired outcomes for the identified Stakeholders.

 
 
 
 
 
 President of The Foundation for Sustainable Communities & Sr. Adjunct Professor

 
 
 Deborah Hagar, MBA

 
 
 595

 
 
 Again, the clear accountability that the initial problems are resolved, without a zero-sum game of negative impact on select stakeholders, will result in desired outcomes AND effective Stakeholder Capitalism.

 
 
 
 
 2

 
 
 Bayana Corporation

 
 
 Joseph S. Bayana

 
 
 198

 
 
 to cultivate trust --- There is an assumption that artificial intelligence has big data, and these big data has equal representation. AI can be "trusted" only if the big data is actual and real-world based.

 
 
 
 
 
 Baya

... (truncated, 98 KB total)

Resource ID: 5697844765df8988 | Stable ID: NjBhYjgzYz