403
Sorry!!
Error! We're sorry, but the page you were looking for doesn't exist.
Veritaschain Standards Organization Shares Non-Normative Technical Note With ETSI TC ESI
(MENAFN- EIN Presswire) EINPresswire / -- VeritasChain Standards Organization (VSO), a non-profit and vendor-neutral technical standards body, today announced that it has shared an informational, non-normative technical note with ETSI TC ESI (Electronic Signatures and Infrastructures).
The document, titled“Electronic Evidence Considerations for AI-Driven System Records: An Illustrative Technical Discussion,” explores, at a conceptual level, how records generated by AI-driven and algorithmic systems may be considered as electronic evidence, and how existing concepts related to electronic signatures, trusted timestamps, and long-term validation could potentially apply. The material was shared strictly as background information and does not constitute a formal ETSI Contribution, a proposal, or a request for any new work item.
As AI-driven systems are increasingly used in regulated and high-stakes environments-such as financial trading, automated decision systems, and AI-assisted operational processes-the records they generate may later be examined in audits, investigations, or dispute resolution. While operational logs are essential for diagnostics and monitoring, electronic evidence implies a higher evidentiary threshold, including demonstrable integrity, attribution, temporal ordering, and long-term verifiability.
VSO's technical note highlights a structural distinction between logs and evidence. Many AI system records were not originally designed for evidentiary use and may rely on proprietary formats, internal signing keys, or system clocks without external attestation. When such records are later presented as evidence, questions of authenticity and integrity may arise that internal logs alone cannot independently address. The document frames this observation as a general technical consideration rather than a critique of any specific practice.
The discussion is explicitly non-prescriptive. It does not define electronic signature formats, trust service requirements, validation procedures, or regulatory interpretations, nor does it suggest modifications to existing ETSI specifications. Instead, it observes that concepts already developed within ETSI TC ESI-such as digital signatures for attribution, trusted timestamps for temporal evidence, long-term validation, and evidence preservation-may offer useful building blocks when considering the evidentiary characteristics of AI-generated records.
“Treating AI system records as potential electronic evidence raises technical questions that go beyond day-to-day logging,” said a representative of VeritasChain Standards Organization.“In evidentiary contexts, the issue is not only what was recorded, but whether those records can withstand independent scrutiny years later. This informational note was shared to support technical dialogue on that question, not to propose standards or outcomes.”
VSO operates as a non-profit, vendor-neutral standards organization and does not engage in lobbying, policy advocacy, or commercial endorsement. Its work focuses on the design and publication of open technical specifications and reference materials related to verifiable audit trails, provenance, and third-party verifiability for AI- and algorithmic-driven systems. The informational sharing with ETSI TC ESI reflects VSO's restrained approach to standards engagement: contributing carefully scoped technical perspectives while respecting existing institutional processes and membership frameworks.
About VeritasChain Standards Organization (VSO)
VeritasChain Standards Organization is a non-profit, vendor-neutral technical standards body focused on verifiable auditability, provenance, and evidentiary integrity for AI- and algorithmic-driven systems. VSO develops open technical specifications and reference materials intended to support transparency, accountability, and long-term trust in high-risk AI applications. VSO does not provide regulatory interpretations, compliance guarantees, or endorsements.
The document, titled“Electronic Evidence Considerations for AI-Driven System Records: An Illustrative Technical Discussion,” explores, at a conceptual level, how records generated by AI-driven and algorithmic systems may be considered as electronic evidence, and how existing concepts related to electronic signatures, trusted timestamps, and long-term validation could potentially apply. The material was shared strictly as background information and does not constitute a formal ETSI Contribution, a proposal, or a request for any new work item.
As AI-driven systems are increasingly used in regulated and high-stakes environments-such as financial trading, automated decision systems, and AI-assisted operational processes-the records they generate may later be examined in audits, investigations, or dispute resolution. While operational logs are essential for diagnostics and monitoring, electronic evidence implies a higher evidentiary threshold, including demonstrable integrity, attribution, temporal ordering, and long-term verifiability.
VSO's technical note highlights a structural distinction between logs and evidence. Many AI system records were not originally designed for evidentiary use and may rely on proprietary formats, internal signing keys, or system clocks without external attestation. When such records are later presented as evidence, questions of authenticity and integrity may arise that internal logs alone cannot independently address. The document frames this observation as a general technical consideration rather than a critique of any specific practice.
The discussion is explicitly non-prescriptive. It does not define electronic signature formats, trust service requirements, validation procedures, or regulatory interpretations, nor does it suggest modifications to existing ETSI specifications. Instead, it observes that concepts already developed within ETSI TC ESI-such as digital signatures for attribution, trusted timestamps for temporal evidence, long-term validation, and evidence preservation-may offer useful building blocks when considering the evidentiary characteristics of AI-generated records.
“Treating AI system records as potential electronic evidence raises technical questions that go beyond day-to-day logging,” said a representative of VeritasChain Standards Organization.“In evidentiary contexts, the issue is not only what was recorded, but whether those records can withstand independent scrutiny years later. This informational note was shared to support technical dialogue on that question, not to propose standards or outcomes.”
VSO operates as a non-profit, vendor-neutral standards organization and does not engage in lobbying, policy advocacy, or commercial endorsement. Its work focuses on the design and publication of open technical specifications and reference materials related to verifiable audit trails, provenance, and third-party verifiability for AI- and algorithmic-driven systems. The informational sharing with ETSI TC ESI reflects VSO's restrained approach to standards engagement: contributing carefully scoped technical perspectives while respecting existing institutional processes and membership frameworks.
About VeritasChain Standards Organization (VSO)
VeritasChain Standards Organization is a non-profit, vendor-neutral technical standards body focused on verifiable auditability, provenance, and evidentiary integrity for AI- and algorithmic-driven systems. VSO develops open technical specifications and reference materials intended to support transparency, accountability, and long-term trust in high-risk AI applications. VSO does not provide regulatory interpretations, compliance guarantees, or endorsements.
Legal Disclaimer:
MENAFN provides the
information “as is” without warranty of any kind. We do not accept
any responsibility or liability for the accuracy, content, images,
videos, licenses, completeness, legality, or reliability of the information
contained in this article. If you have any complaints or copyright
issues related to this article, kindly contact the provider above.
Most popular stories
Market Research
More Story
Comments
No comment