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Glossary

Consent artifact

Consent artifact means a record showing that a contributor or site granted permission for data capture and downstream use. The term matters because it turns a model or procurement concept into concrete data requirements you can evaluate samples against.

Updated 2026-05-04
By truelabel
Reviewed by truelabel ·
consent artifact
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Quick facts

GDPR Article 7
Where processing is based on consent, the controller must be able to demonstrate that the data subject has consented (EU 2016/679).
ODRL (W3C)
Open Digital Rights Language — formal model for permissions, prohibitions, and duties attached to digital assets (W3C Recommendation, 2018).
C2PA Content Credentials
Cryptographic provenance + consent assertions; Adobe, Microsoft, BBC, Sony, Truepic among adopters.
Datasheets for Datasets
arXiv:1803.09010 (Gebru et al., 2018) — collection-process and contributor questions that double as consent documentation.
What a real consent artifact carries
Contributor identity (or pseudonymous ID), capture session ID, allowed uses, scope (specific commercial use), withdrawal terms, signature/timestamp, audit trail.

Comparison

QuestionAnswer
Where it appearsSourcing specs, QA requirements, dataset manifests, and buyer review notes
Why it mattersIt turns abstract AI language into a supplier-verifiable requirement
Common failureUsing the term without defining modality, format, rights, or acceptance criteria

How to use this term in a spec

A consent artifact is a record that lets the buyer verify that capture participants or sites granted permission for the data use being purchased. GDPR Article 7 states that a controller relying on consent must be able to demonstrate that consent was given. [1]

What to avoid

Do not use consent artifact as a vague keyword. Define the data files, metadata, rights, QA checks, and delivery format that make it measurable.

Consent artifact in buyer review

In a sourcing request for physical AI, the artifact should connect consent to a contributor, location, capture session, allowed uses, and withdrawal or restriction terms. ODRL provides a rights-expression model, while Datasheets and dataset cards show how consent and collection context can be documented alongside dataset delivery. [2] [3] [4]

Consent artifact supplier evidence

Supplier samples should include redacted examples of consent records before private-space or identifiable-person data is accepted. A vague statement that contributors were informed is not a consent artifact unless it is tied to auditable metadata.

Related pages

Use these to move from category-level context into specific task, dataset, format, and comparison detail.

Physical AI glossaryGlossary hubData provenanceDefinition and terminologyEgocentric dataDefinition and terminologyOff-the-shelf datasetDefinition and terminologyPhysical AI training dataDefinition and terminologyRobot demonstrationsDefinition and terminologySim-to-real gapDefinition and terminologyTeleoperation dataDefinition and terminology

External references and source context

  1. GDPR Article 7 — Conditions for consent

    GDPR Article 7 requires controllers to be able to demonstrate that a data subject gave consent when processing is based on consent.

    GDPR-Info.eu ↩
  2. ODRL Information Model 2.2

    ODRL provides a model for expressing permissions, prohibitions, and duties attached to digital assets.

    W3C ↩
  3. Datasheets for Datasets

    Datasheets for Datasets includes collection process and distribution questions that can document consent and rights context.

    arXiv ↩
  4. Dataset cards are not yet standardized for physical AI procurement

    Dataset cards provide a structured place to document collection, intended use, and limitations for datasets.

    Hugging Face ↩

More glossary terms

Data provenanceTraceability metadata: source, consent, rights, capture conditions, chain of custody.Egocentric dataFirst-person camera footage capturing how a worker or operator sees a task.Off-the-shelf datasetAn existing public or commercial dataset bought without custom collection.Physical AI training dataData that teaches models to perceive, reason about, and act in physical environments.Robot demonstrationsRecorded successful task executions used as demonstrations for imitation learning.Sim-to-real gapThe drop in policy performance when transferring from simulation to physical robots.

FAQ

What is Consent artifact?

Consent artifact is a record showing that a contributor or site granted permission for data capture and downstream use.

Why does it matter for physical AI?

It matters because physical AI data must be connected to actions, environments, metadata, rights, and model use, not just raw files.

How should buyers spec it in a sourcing request?

Attach contributor consent expectations to every sourcing request involving identifiable people or private spaces.

Can suppliers validate this from samples?

Yes, if the buyer defines visible evidence, metadata requirements, and acceptance criteria before suppliers submit files.

Find datasets covering consent artifact

Truelabel surfaces vetted datasets and capture partners working with consent artifact. Send the modality, scale, and rights you need and we route you to the closest match.

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