HGCP: A Voluntary Signing Framework for Human Expression in the Age of AI
draft-taoqiwen-hgcp-00

Network Working Group                                             Q. Tao
Internet-Draft                                    Independent Researcher
Intended status: Informational                             30 March 2025
Expires: 1 October 2025

 HGCP: A Voluntary Signing Framework for Human Expression in the Age of
                                   AI
                         draft-taoqiwen-hgcp-00

Abstract

   In an era where AI-generated content has become indistinguishable
   from human writing, the Human-Generated Content Protocol (HGCP)
   proposes a voluntary signing framework that enables human authors to
   take responsibility for their expressions.  Instead of relying on
   probabilistic detection methods or enforcing centralized identity,
   HGCP encourages a simple yet powerful act: a signer publicly declares
   responsibility for authored content through a structured signature
   block.  The protocol is platform-neutral, supports both real-name and
   anonymous identities, and prioritizes transparency, accountability,
   and human agency.  HGCP defines minimal signature structures,
   integration suggestions for platforms and tools, and philosophical
   guidance for fostering expression trust in an increasingly synthetic
   information ecosystem.

About This Document

   This note is to be removed before publishing as an RFC.

   Status information for this document may be found at
   https://datatracker.ietf.org/doc/draft-taoqiwen-hgcp/.

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   This Internet-Draft will expire on 1 October 2025.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  The Problem of Expression Trust . . . . . . . . . . . . . . .   3
   3.  The Philosophy of HGCP: Responsibility Over Provenance  . . .   4
   4.  Signature Declaration Structure . . . . . . . . . . . . . . .   5
   5.  Identity Types and Trust Levels . . . . . . . . . . . . . . .   7
     5.1.  Statement Responsibility Levels . . . . . . . . . . . . .   7
   6.  Platform and Tool Integration Suggestions . . . . . . . . . .   8
   7.  Social and Ethical Considerations . . . . . . . . . . . . . .   9
   8.  Example Use Cases . . . . . . . . . . . . . . . . . . . . . .  10
     8.1.  Personal Blogs and Essays (identity_type: pseudonymous,
           statement_level: HGCP-H)  . . . . . . . . . . . . . . . .  10
     8.2.  Social Media Discussion (identity_type: anonymous,
           statement_level: HGCP-H)  . . . . . . . . . . . . . . . .  10
     8.3.  Academic or Scientific Blog Summary (identity_type:
           real-name, statement_level: HGCP-C) . . . . . . . . . . .  11
     8.4.  AI-Assisted Script Writing (identity_type: human+ai,
           statement_level: HGCP-H+AI) . . . . . . . . . . . . . . .  11
     8.5.  AI-Generated Content Disclosure (identity_type: ai,
           statement_level: HGCP-AI) . . . . . . . . . . . . . . . .  11
   9.  Criticisms and Responses  . . . . . . . . . . . . . . . . . .  12
     9.1.  Criticism 1: “Signing doesn’t stop misinformation.” . . .  12
     9.2.  Criticism 2: “Malicious actors can sign too.” . . . . . .  12
     9.3.  Criticism 3: “Why not require real names?”  . . . . . . .  12
   10. Scope and Limits of Human Responsibility  . . . . . . . . . .  12
   11. Why We Need HGCP Now  . . . . . . . . . . . . . . . . . . . .  13
   12. Future Extensions and Evolving Use Cases  . . . . . . . . . .  13
   13. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  14
   14. Security Considerations . . . . . . . . . . . . . . . . . . .  14
   15. Informative References  . . . . . . . . . . . . . . . . . . .  15
   Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . .  16
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .  16

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1.  Introduction

   In the rapidly evolving digital world, a flood of content from
   countless sources fills our screens—much of it now automatically
   generated, indistinguishable, and detached from genuine human intent.
   As artificial intelligence becomes increasingly proficient at
   mimicking human expression, the boundary between real thought and
   algorithmic generation is becoming ever more blurred.  The rise of
   AI-generated content brings tremendous opportunity, but it also
   presents a critical question: if we can no longer identify who wrote
   something, how can we trust it?

   The Human-Generated Content Protocol (HGCP) is proposed as a
   voluntary signing framework to address this issue.  HGCP does not
   attempt to detect AI content through technical means; instead, it
   introduces a simple yet powerful idea: that a human author should be
   able to voluntarily declare, "This was written by me, and I take
   responsibility for it."

   HGCP is not a detection algorithm or classification tool.  It is a
   social and ethical trust mechanism.  It provides a standardized
   signing format that enables any publisher—across any platform and
   identity type—to assert authorship in a verifiable and human-
   responsible manner.  HGCP is platform-neutral, identity-flexible, and
   supports both anonymous and real-name authors who wish to make their
   human expression distinguishable and trustworthy.

   HGCP is intentionally designed as a minimal core protocol—simple,
   declarative, and human-first.  It does not attempt to encode all
   possible expression scenarios from the start.  Instead, it offers a
   stable foundation that can evolve over time to support multi-signer
   declarations, partial claims, multimedia expressions, and richer
   trust semantics.

2.  The Problem of Expression Trust

   The internet was originally built to foster human connection and
   communication.  Yet in a world where content creation, duplication,
   and distribution approach zero cost, the origin of information has
   become increasingly obscured.  We once relied on domain names,
   writing style, and user profiles to infer trustworthiness—but now,
   all of these can be simulated or spoofed by AI.

   We face a growing asymmetry: it is far easier to generate content
   than to verify its trust.  This leads not only to an explosion of
   noise and manipulation but to a slow erosion of meaning itself.
   Readers hesitate to believe; authors hesitate to sign their work;
   platforms hesitate to take responsibility.

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   Many recent solutions have focused on "AI detection"—using machine
   learning classifiers to guess whether a given text was written by an
   AI.  These tools are inherently probabilistic, easily evaded, and
   perpetually behind in the arms race of model advancement.  The more
   essential question is not "Was this written by an AI?", but rather:
   "Is someone willing to take human responsibility for having said
   this?"

   HGCP addresses this deeper layer: the level of expression
   responsibility.  It introduces a new kind of signal—not derived from
   how content was generated, but from whether someone is willing to
   stand behind it.  In doing so, trust becomes not a passive inference
   but an active, verifiable commitment.

3.  The Philosophy of HGCP: Responsibility Over Provenance

   The core idea of HGCP is not to verify originality, authorship, or
   human origin of content—but to offer a voluntary, structured
   mechanism for a person to take public responsibility for their
   expression.

   Whereas most classification systems ask "Who wrote this?", HGCP
   invites a more meaningful question: "Are you willing to claim this
   expression as your own?"

   Signing under HGCP does not imply that the content is accurate, high-
   quality, or original.  It simply affirms: "I am a human being, and I
   am publicly acknowledging that I wrote this."

   This makes HGCP signing a social gesture rather than a technical
   classification.  It is not about improving detection precision, but
   about restoring the most basic principle of communication: to speak
   is to bear responsibility.

   HGCP is not anti-AI.  It does not forbid AI-assisted writing.  Its
   purpose is not to exclude AI, but to identify human intent and
   responsibility.  Even if a human uses AI to assist, as long as they
   willingly sign, they are taking responsibility as a human.

   HGCP is an open framework.  It does not restrict what tools you use;
   it only asks whether you are willing to sign.  It does not judge your
   expertise; it only values your readiness to be held accountable.
   This voluntary human claim becomes the root signal of trust in HGCP.

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4.  Signature Declaration Structure

   HGCP recommends that any author willing to assume responsibility for
   their expression include a standardized signature declaration when
   publishing content.  The declaration should contain the following
   elements:

   Required Fields:

   signer_id: A pen name, public key fingerprint, platform username, or
   other verifiable identity reference (RFC 9580 [RFC9580] OpenPGP
   fingerprints recommended)

   timestamp: A UTC timestamp indicating when the signature was made
   (preferably in [RFC3339] format)

   content_hash: A cryptographic digest of the original text using a
   standard hash function (SHA-256 recommended, as defined in [RFC6234])

   hgcp_version: A required version field to indicate which version of
   the HGCP signature structure is being used (e.g., "0.2").  This helps
   ensure future compatibility as the protocol evolves.

   declaration: A clear statement of responsibility, e.g., "I affirm
   that the above content was written by me and I accept responsibility
   for it."

   Optional Fields:

   tools_used: If any tools (AI assistants, grammar correctors,
   translation engines) were involved, list them transparently

   identity_type: e.g., real-name, anonymous, pseudonymous,
   organizational

   revocability: Whether the signature can be withdrawn or the content
   edited.  Suggested standard values include:
   - immutable
   - editable-until-locked
   - time-limited-editable
   - revocable-with-proof

   id_format: e.g., "GitHub username", "PGP fingerprint", "platform
   alias"

   Example Signature (Markdown):

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   Author: Tao Qiwen
   Timestamp: 2025-03-29T14:22Z
   HGCP Version: 0.2
   ID Type: anonymous
   Tools Used: ChatGPT + manual edits
   Content Hash (SHA-256, base64): aGVsbG8sIHdvcmxk...
   Revocability: editable-until-locked
   Declaration: I confirm that the above content was published by me,
   and I take responsibility as a human author.

   Example HGCP Signature (JSON, v0.1):

   { "signer_id": "qiwen2025", "id_type": "anonymous", "timestamp":
   "2025-03-29T14:22Z", "hgcp_version": "0.2", "content_hash":
   "a732c8dffe34aabbcc...", "tools_used": ["ChatGPT", "Notion AI"],
   "revocability": "editable-until-locked", "declaration": "I confirm
   that the above content was published by me, and I take responsibility
   as a human author." }

   Optional (PGP Signature):

   "gpg_signature": "-----BEGIN PGP SIGNATURE-----\n...\n-----END PGP
   SIGNATURE-----"

   HGCP signatures are versioned to ensure clarity, compatibility, and
   future evolution.  The hgcp_version field in the signature block
   indicates which structure is used.

   *  *v0.1*: Basic HGCP signature, including signer ID, timestamp,
      content hash, and a declaration.  Suitable for human-readable
      contexts (e.g., Markdown).

   *  *v0.2*: Adds optional cryptographic signing (e.g., PGP) for
      enhanced verification.  Fully backward-compatible with v0.1.

   "hgcp_version": "0.2"

   The version number refers to the signature structure specification,
   not the tool version or software implementation.  Future versions may
   include DID bindings, cross-platform trust references, or encrypted
   metadata.

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5.  Identity Types and Trust Levels

   HGCP does not require real-name identification, but encourages the
   use of consistent and interpretable identity labels.  Each
   identity_type is associated with a general trust signal, though long-
   term behavior and signing consistency are more important than any
   single declaration.

   *Identity Types and Suggested Trust Levels*

      *human*
      A human author who signs and takes responsibility.
      *Trust Level:* High

      *human+ai*
      A human-led expression with AI assistance.
      *Trust Level:* Medium-High

      *organization*
      A collective statement signed on behalf of an entity.
      *Trust Level:* Medium

      *anonymous*
      An identity with no disclosed name but consistent signing history.
      *Trust Level:* Medium

      *ai*
      Clearly labeled as AI-generated, signature for transparency only.
      *Trust Level:* Low

   Even anonymous users may build trust over time through persistent and
   verifiable signing behavior.  Platforms may choose to highlight
   signer identity history to assist readers in evaluating context.

5.1.  Statement Responsibility Levels

   The statement_level field reflects how the signer claims
   responsibility for the content.  It does not attempt to verify
   authorship origin, but instead signals how the signer relates to the
   text and its expression.

   *Statement Levels and Their Meanings*

      *HGCP-H*
      Human-only authored, signer claims full responsibility
      _Use Case:_ Essays, personal writings

      *HGCP-H+AI*

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      Human-led with AI assistance, signer reviews and owns final
      version
      _Use Case:_ Blogs, mixed content

      *HGCP-O*
      Statement signed on behalf of an organization
      _Use Case:_ Press releases, company updates

      *HGCP-AI*
      AI-generated content, signed only for transparency
      _Use Case:_ Automated posts, system replies

      *HGCP-C*
      Curated or reinterpreted content, signer takes responsibility for
      context and presentation
      _Use Case:_ Compilations, summaries, quoted content

   Platforms and readers may interpret these statement levels in
   combination with identity and signing history to infer credibility or
   accountability.  HGCP does not enforce strict verification, but
   rather enables visible patterns of declared responsibility. ###Trust
   is Accumulated Through Behavior

   HGCP emphasizes the act of voluntarily claiming responsibility, not
   the technical origin of the content.  Repeated, consistent, and
   transparent signing behavior is more meaningful than a single
   signature.  Platforms are encouraged to experiment with trust scoring
   systems based on:

   *  Identity stability

   *  Revocation or editing history

   *  Contradiction or refutation patterns

   *  Peer endorsement or community validation

6.  Platform and Tool Integration Suggestions

   HGCP is platform-neutral and decentralized, but content platforms,
   publishing tools, and browser extensions are encouraged to integrate
   HGCP through the following actions:

   For content platforms:

   Provide HGCP signing support (e.g., auto-generate timestamp, content
   hash, signature block)

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   Visibly display signature declarations and identity type

   Offer exportable signature metadata (e.g., JSON-LD)

   Provide "verify signature" buttons for end users

   Allow flagging or auditing of forged or misleading signatures

   For authoring tools:

   Markdown/word editors can embed HGCP plugins for local signing

   AI-assisted writing apps should encourage users to optionally sign
   with responsibility

   Publishing interfaces should invite voluntary HGCP signing at
   submission time

   For reader tools and plugins:

   Browser extensions can detect and visually mark HGCP-signed content

   Enable readers to view signer reputation, signature validity, and
   signing history

7.  Social and Ethical Considerations

   HGCP is not a replacement for content governance, but a voluntary
   signal system designed to restore visibility to human-authored
   expressions in an increasingly hybrid content landscape.

   HGCP does NOT:

   Detect AI content or act as an AI classifier

   Track real identities or force doxxing

   Judge truth, originality, or value of signed content

   Restrict unsigned content from being published

   HGCP DOES protect:

   Anonymous authors’ right to claim authorship

   Signers’ right to choose their identity level

   The right to revoke, edit, or update signed content

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   Each platform’s autonomy in adapting or extending HGCP support

   HGCP offers a decentralized path to expression accountability—not by
   censorship, but by providing those who want to be recognized and
   trusted the ability to do so.

8.  Example Use Cases

   HGCP is platform-neutral and supports a wide spectrum of content
   styles and identities.  Each use case involves a signer voluntarily
   declaring both their identity context and expression responsibility.

8.1.  Personal Blogs and Essays (identity_type: pseudonymous,
      statement_level: HGCP-H)

   A blogger writing longform essays under a pseudonym includes a
   signature at the end of each post.  While the views may be
   subjective, the signer affirms personal responsibility for all
   content.

   { "signer_id": "silentvoice", "id_type": "pseudonymous",
   "statement_level": "HGCP-H", "timestamp": "2025-03-29T16:12Z",
   "tools_used": [], "declaration": "I wrote the above post entirely on
   my own and stand by it as a human author." }

8.2.  Social Media Discussion (identity_type: anonymous,
      statement_level: HGCP-H)

   An anonymous user on a contentious Reddit thread wants to show that
   they are not a bot and take personal responsibility for their words.

      "This opinion is signed under HGCP.  I take responsibility for
      this view as a human author."

   The signature metadata may look like:

   { "signer_id": "anon321", "id_type": "anonymous", "statement_level":
   "HGCP-H", "timestamp": "2025-03-29T17:35Z", "tools_used": [],
   "declaration": "I stand by this statement as an individual human
   participant in this conversation." }

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8.3.  Academic or Scientific Blog Summary (identity_type: real-name,
      statement_level: HGCP-C)

   A university researcher summarizes a recent paper from another lab
   and posts it to their department blog.  While they didn't generate
   the original content, they take responsibility for the summary.

   { "signer_id": "dr.lin", "id_type": "real-name", "statement_level":
   "HGCP-C", "timestamp": "2025-03-29T19:12Z", "tools_used": ["Notion",
   "Grammarly"], "declaration": "This post is my own summary of a
   published paper.  While I did not author the original, I take
   responsibility for this interpretation and presentation." }

8.4.  AI-Assisted Script Writing (identity_type: human+ai,
      statement_level: HGCP-H+AI)

   A YouTube creator uses ChatGPT to help draft a video script.  They
   edit, restructure, and rewrite sections before publication.

   { "signer_id": "creatorzone", "id_type": "human+ai",
   "statement_level": "HGCP-H+AI", "timestamp": "2025-03-29T21:05Z",
   "tools_used": ["ChatGPT", "DeepL", "Grammarly"], "declaration": "This
   script was generated with AI assistance, but I have reviewed and
   edited the final version and take human responsibility for it." }

8.5.  AI-Generated Content Disclosure (identity_type: ai,
      statement_level: HGCP-AI)

   A system-generated bot post discloses that it is not written by a
   human, but still includes HGCP metadata for transparency and
   traceability.

   { "signer_id": "autosummary-bot", "id_type": "ai", "statement_level":
   "HGCP-AI", "timestamp": "2025-03-29T23:00Z", "tools_used": ["Custom
   NLP Pipeline"], "declaration": "This content was automatically
   generated by a bot and is signed for transparency purposes only." }

   These examples demonstrate how HGCP enables a wide range of
   expressive behaviors, from pseudonymous essays to AI-generated system
   messages.  By combining identity_type, statement_level, and an
   explicit declaration, HGCP makes the nature of authorship visible,
   responsibility claimable, and trust interpretable.

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9.  Criticisms and Responses

   As a voluntary protocol, HGCP is not without its skeptics.  Below are
   common concerns and clarifications to address them:

9.1.  Criticism 1: “Signing doesn’t stop misinformation.”

   *Response:* Correct.  HGCP is not a fact-checking mechanism or a tool
   for moderating content.  It exists to signal that a human is willing
   to be associated with and take responsibility for the
   expression—regardless of whether others agree with it.

9.2.  Criticism 2: “Malicious actors can sign too.”

   *Response:* HGCP does not prevent bad-faith actors from signing.
   However, consistent signing behavior creates a trackable pattern,
   enabling communities to build reputation graphs over time.
   Persistent abuse can be observed, flagged, and judged accordingly.

9.3.  Criticism 3: “Why not require real names?”

   *Response:* HGCP protects the right to pseudonymous and anonymous
   expression.  Real-name identification is not always safe, especially
   in authoritarian contexts.  Responsibility can still be claimed
   meaningfully without revealing legal identities.

   HGCP emphasizes *voluntary, transparent, and repeatable* expression
   behavior.  It complements—but does not replace—legal, social, or
   technical forms of accountability.

10.  Scope and Limits of Human Responsibility

   HGCP affirms an ethical gesture of responsibility, but it is not a
   legal instrument.  Signing indicates that the author:

   *  Is human (or self-identifies as such),

   *  Chooses to claim the expression,

   *  Accepts the social consequences of that claim.

   However, the scope of “responsibility” should be clearly understood:

   *  HGCP *does not confer legal liability* unless enforced by separate
      legal agreements or jurisdictions.

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   *  HGCP *does not guarantee truth, originality, or moral
      correctness*.

   *  HGCP *does allow for revocation*, and platforms may record and
      display revocation histories transparently.

   Over time, frequent revocations or inconsistency in signing behavior
   may reduce the perceived trustworthiness of a signer.  Platforms and
   readers are encouraged to interpret such patterns thoughtfully.

   HGCP serves as a *signal*, not a sentence.  It is a flag of
   presence—not proof of virtue.

11.  Why We Need HGCP Now

   In an era where synthetic content floods our screens and truth feels
   elusive, what we are losing is not just facts—but responsibility.

   Expression has never merely been about information.  It is about
   standing behind what one says.

   HGCP is a quiet signal.  It is not a firewall or detection tool, but
   a torch, held by those willing to say:

   "This is what I said.  And I am willing to be remembered for it."

   Those who sign are not necessarily perfect, but they are present.
   They are not hiding.  They are accountable.

   HGCP does not aim to stop AI, nor does it attempt to verify the
   origin or value of content.  Instead, it offers a decentralized and
   consistent way for humans to voluntarily claim authorship and
   responsibility.

   Just as HTTPS creates trust in communication, HGCP creates trust in
   expression—not by policing the source, but by making visible those
   who choose to stand behind their words.

   In an age of artificial voice, those who remain human by choice will
   be trusted first.

12.  Future Extensions and Evolving Use Cases

   HGCP is deliberately minimal by design.  Its current version focuses
   on text-based, single-signer declarations of human responsibility.
   However, real-world content and trust environments are far more
   diverse.  Future protocol versions may support:

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   *  Multi-signer declarations (e.g., co-authorship, joint statements)

   *  Partial responsibility claims (e.g., hybrid AI + human paragraph-
      level tags)

   *  Multimedia content hashes (e.g., audio, image, or video
      signatures)

   *  Publisher-declared AI content without human responsibility

   *  Role-based identity claims (e.g., editor, translator, commentator)

   *  Richer metadata for curatorial or interpretive context

   HGCP will evolve cautiously.  Its core principle remains:
   responsibility, voluntarily claimed, should be visible and
   interpretable.  Extensions should enhance this clarity—not dilute it.

13.  IANA Considerations

   This document has no IANA actions.

14.  Security Considerations

   HGCP does not introduce new network protocols or data exchange
   layers, and thus does not pose direct technical threats such as
   injection, eavesdropping, or man-in-the-middle attacks.  However, it
   introduces indirect risks rooted in the potential misuse,
   manipulation, or misunderstanding of signature claims.  These risks
   are primarily social and structural in nature, rather than
   cryptographic.

   Key risks include:

   Identity Impersonation and Signature Forgery

   In the absence of strong cryptographic validation (e.g., OpenPGP
   signatures), it is possible for malicious actors to forge HGCP-style
   declarations using arbitrary signer IDs.  Platforms should support
   optional cryptographic signing or verified identity bindings (e.g.,
   platform-verified accounts) to mitigate impersonation and provide
   trustworthy signature attribution.

   Mass Signature Automation (Sybil Attacks)

   Without rate limits or identity constraints, attackers could mass-
   generate AI content paired with fabricated signature blocks to
   simulate trustworthiness at scale.  This undermines the value of

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   human-authored declarations.  To address this, platforms may
   implement frequency controls, account reputation checks, or trust
   graphs to detect and contain such behavior.

   Content Hash Evasion through Minimal Edits

   HGCP relies on cryptographic content hashes to bind declarations to
   content.  Yet even trivial edits (e.g., changing a space or emoji)
   produce a different hash, potentially allowing near-identical but
   unsigned derivatives to circulate unchallenged.  Platforms are
   encouraged to store content snapshots alongside signatures, or
   explore fuzzy hashing techniques to detect close variants of signed
   material.

   Revocation Abuse and Responsibility Avoidance

   HGCP supports revocable or editable signature declarations, which can
   enhance flexibility—but also invite strategic denial or erasure of
   public statements.  To preserve accountability, platforms should
   retain and display signature histories, including revocation
   timestamps, and clearly indicate whether a signed expression has been
   withdrawn or altered post-publication.

   Lack of Native Trust Scoring or Validation Layer

   HGCP intentionally avoids enforcing a centralized trust model.  While
   this encourages openness, it also requires platforms and communities
   to build supplementary mechanisms for evaluating signer credibility,
   such as reputation systems, signature consistency tracking, or peer
   endorsement.  Transparency in how these trust layers are constructed
   is essential to avoid unintended bias or exclusion.

   Ultimately, HGCP’s effectiveness hinges not on cryptographic
   certainty, but on the visible willingness of authors to claim
   responsibility and the surrounding ecosystem’s support for
   interpretation, verification, and dispute resolution.  It is a
   voluntary, human-centered protocol—its security lies in
   participation, not enforcement.

15.  Informative References

   [RFC3339]  Klyne, G. and C. Newman, "Date and Time on the Internet:
              Timestamps", RFC 3339, DOI 10.17487/RFC3339, July 2002,
              <https://www.rfc-editor.org/rfc/rfc3339>.

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Internet-Draft                    HGCP                        March 2025

   [RFC6234]  Eastlake 3rd, D. and T. Hansen, "US Secure Hash Algorithms
              (SHA and SHA-based HMAC and HKDF)", RFC 6234,
              DOI 10.17487/RFC6234, May 2011,
              <https://www.rfc-editor.org/rfc/rfc6234>.

   [RFC9580]  Wouters, P., Ed., Huigens, D., Winter, J., and Y. Niibe,
              "OpenPGP", RFC 9580, DOI 10.17487/RFC9580, July 2024,
              <https://www.rfc-editor.org/rfc/rfc9580>.

Acknowledgments

   This document was initially drafted using ChatGPT (OpenAI), and
   subsequently edited and approved by the human signer.  The signer
   acknowledges responsibility for the final content.

Author's Address

   Qiwen Tao
   Independent Researcher
   Email: natureconservation@yeah.net

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