IEEE P3152/D1, Aug 2023 PDF | Request Standard
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IEEE P3152/D1, Aug 2023

IEEE Draft Standard for Transparent Agency Identification of Humans and Machines

Standard by IEEE, 2023

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  • Availability: Immediate Download
  • Language: English
  • License Type: Single User
  • Updates: Not Included
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  • Language: English
  • License Type: Enterprise / Multi User
  • Updates: Included

About This Item

Legal Notices*

IEEE P3152/D1, Aug 2023 is a draft standard focused on transparent agency identification of humans and machines in computing and processing environments. It addresses how identity can be represented, distinguished, and communicated in technical systems where human and machine actions may need to be clearly separated. That matters for system design, records, trust, and operational clarity, especially when automated and human-driven processes interact within the same workflow.

About IEEE P3152/D1, Aug 2023

IEEE P3152/D1, Aug 2023 appears to define draft requirements or guidance for identifying whether a participant, device, or process is acting as a human or a machine. In a computing context, that can support clearer attribution, traceability, and interoperable handling of identity-related information. As a draft technical document, it is most relevant to engineers, architects, and compliance teams reviewing identity signals, agency labeling, or related data exchange practices.

Where is IEEE P3152/D1, Aug 2023 used?

This standard is most likely relevant in digital systems that manage identity, access, or event attribution, including software platforms, automated decision workflows, and machine-assisted services. IEEE P3152/D1, Aug 2023 may also be useful where logs, transactions, or user interactions need to show whether a human or an automated agent initiated an action. That can apply to enterprise computing, connected services, and other environments where clear agency identification supports reliable processing and review.

Importance in practice

In practice, IEEE P3152/D1, Aug 2023 can help reduce ambiguity in technical records and improve consistency across systems that must distinguish human activity from machine activity. Clear identification supports design control, testing, auditing, and procurement decisions when agency labeling is part of the requirement set. It may also reduce implementation risk by giving teams a common reference for how transparent identification should be handled in computing and processing applications.

  • Transparent human-versus-machine identification
  • Computing and processing context
  • Draft requirements for agency labeling
  • Traceability in system records
  • Support for review, testing, and compliance
SKU: 5073ade73071

  • Publication Date: 2023
  • Standard Status: Inactive
  • Publisher: IEEE
  • Subject: Computing and Processing
  • Official IEEE: Doi link
  • New Version Available: P3152 (2024)
  • Previous Version: P3152 (2024)
  • Previous Version: P3152 (2024)
  • This Version: P3152 (2023)

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