Canada’s federal government has just released an early version of the AI Register it promised after its election earlier this year.
An AI Register is an important transparency tool – it will help researchers and the broader public understand what AI-enabled tools are in use in the federal public sector and provides basic information about them. The government also intends the register to be a resource for the public sector – allowing different departments and agencies to better see what others are doing so as to avoid duplication and to learn from each other.
The information accompanying the Register (which is published on Canada’s open government portal) indicates that this is a “Minimum Viable Product”. This means that it is “an early version with only basic features and content that is used to gather feedback.” It will be interesting to see how it develops over time.
One interesting aspect of the register is that it states that it was “assembled from existing sources of information, including Algorithmic Impact Assessments, Access to Information requests, responses to Parliamentary Questions, Personal Information Banks, and the GC Service Inventory.” Since it contains 409 entries at the time of writing, and since there are only a few dozen published Algorithmic Impact Assessments (AIAs), this suggests that the database was compiled largely using sources other than AIAs. The reference to access to information requests suggest that some of the data may have been gathered using the TAG Register Canada laboriously compiled by Joanna Redden and her team at the Western University. The sources for the TAG Register also included access to information requests and responses to questions by Members of Parliament. Prior to the development of the federal AI Register, the TAG Register was probably the most important source of information about public sector AI in Canada. The TAG Register is not made redundant by the new AI Register – it contains additional information about the systems derived from the source materials.
The federal AI Register sets out the name of each system and provides a description. It indicates who the primary users are, and which government organization is responsible for it. Other fields provide data about whether the system is designed in-house or is furnished by a vendor (and if so, which one). It also indicates whether the system is in development, in production, or retired. There is a brief description of the system’s capabilities, some information about the data sources used, and an indication of whether it uses personal data. The register also indicates whether users are given notice of use. There is a brief description of the expected outcomes of the system use.
All in all, it’s a good start, and clearly the developers of this database are open to feedback. (For example, I would like to see a link to the Algorithmic Impact Assessment under the Directive on Automated Decision-Making, if such an assessment has been carried out).
This is an important transparency initiative, and it will be a good source of data for researchers interested in public sector AI. It is also an interesting model that provincial governments might want to consider as they also roll out AI use across their public sectors.
