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AI-Assisted Transcription of Indigenous Affairs Historical Records

Accessibility · Research & Development

What it collects that can identify you

Sensitive personal information
Identifiable data
  • The RG10 historical records contain personal information about individuals — including Indigenous people — documented in administrative records of the Department of Indian Affairs and Northern Development. The register confirms the system involves personal information.

Also collects operational data, which is anonymized data.

Run by
Library and Archives Canada (LAC)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization, Me

What it is for

AccessibilityResearch & Development

This system uses AI-powered handwritten text recognition to transcribe approximately six million pages of historical records from the Department of Indian Affairs and Northern Development (the RG10 collection), making them searchable and accessible to the public. It was developed by Library and Archives Canada in partnership with the Canadian Research Knowledge Network and the European company READ-COOP (Transkribus). Because the records document Indigenous history and contain personal information, access and accuracy have significant implications for affected communities. The system has since been retired.

What it collects and what happens to it

Data taken in

Sensitive personal information
Identifiable data
  • The RG10 historical records contain personal information about individuals — including Indigenous people — documented in administrative records of the Department of Indian Affairs and Northern Development. The register confirms the system involves personal information.
Operational data
Anonymized data
  • The primary input is approximately six million scanned page images from the RG10 Collection of Department of Indian Affairs and Northern Development historical records — administrative documents spanning colonial-era Indian Affairs governance.

Processing

Speech & Audio
  • The system employs Intelligent Character Recognition (ICR) and Handwritten Text Recognition (HTR) — machine learning techniques trained to read and transcribe handwritten and printed text from scanned historical documents, with large language model assistance for contextual disambiguation.

What it does

Sensing (Perceptive AI)
Human decides
  • The system perceives and interprets scanned document images using Intelligent Character Recognition (ICR) and Handwritten Text Recognition (HTR), converting visual representations of historical handwritten and printed text into machine-readable transcriptions. Human archivists and researchers review and validate the outputs.
Understanding (Semantic AI)
Human decides
  • Large language model capabilities are applied to improve transcription accuracy and contextual understanding of historical text, enabling better interpretation of ambiguous handwriting, archaic language, and domain-specific terminology in the Indigenous affairs records.

Outputs

Generated content
Anonymized data
  • The system produces machine-readable text transcriptions of handwritten and printed historical document pages. These transcriptions make the RG10 collection searchable and accessible to members of the public, enabling research into Indigenous history.

Run by

Library and Archives Canada (LAC)
  • Library and Archives Canada (LAC) is the federal institution that deployed this transcription system in collaboration with the Canadian Research Knowledge Network (CRKN) to improve access to the RG10 historical records collection.

Government of Canada Algorithmic Impact Register — RG10 Transcription

Built by

READ-COOP SCE
  • READ-COOP, based in Innsbruck, Austria, is the European cooperative that builds and supplies the Transkribus platform — an AI-powered handwritten text recognition tool originating from the EU-funded READ project at the University of Innsbruck. It is the technology vendor for this system.

Government of Canada Algorithmic Impact Register — RG10 Transcription

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Library and Archives Canada retains access to the transcription outputs as part of the RG10 collection management and archival mandate.
Available to me
  • Members of the public, listed as the primary users of the system, can access the transcribed records from the RG10 collection to support research — particularly research relevant to Indigenous history.

Stored

Not stated by the Helpful Places.

How to read the colours

Can it identify you?

Anonymized data
Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous data
Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable data
The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides
This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes
This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous
This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

  • Right to Be Informed of AI UseMembers of the public accessing the RG10 collection through Library and Archives Canada are informed via the register that AI transcription technology (Transkribus/ICR/LLM) was used to produce the searchable text. The system has been retired, so this right applies to understanding historical AI use. Contact Library and Archives Canada for further information.
  • Right to Correct Your DataIf you believe a transcription of a record containing your personal information or information about your family or community contains errors, you may contact Library and Archives Canada to request a correction or to flag the inaccuracy. The register confirms that personal information is involved in this system.

Risks and safeguards

  • Reputational harmOCR and HTR transcription errors in historical documents involving personal information about Indigenous individuals could misrepresent names, events, or facts, causing harm to individuals or communities in the historical record. The involvement of the Canadian Research Knowledge Network and the collaborative development process with archival experts provides some mitigation through domain-specific model training, but no specific error-correction or review process is described in the register entry.
  • Societal & cultural harmThe RG10 collection documents colonial administration of Indigenous peoples in Canada; inaccurate transcriptions could distort the historical record of Indigenous history, communities, and individuals. Collaboration with CRKN and the development of domain-specific recognition models is intended to improve accuracy. However, the register does not describe Indigenous community consultation in the transcription process, which is a significant gap given the cultural sensitivity of the records.