99
edits
Changes
Jump to navigation
Jump to search
mLine 1:
Line 1: + + − As part of the third review, TBS is proposing a series of policy recommendations and accompanying amendments to the directive. The recommendations would help ensure that automated decision systems impacting federal public servants are fair and inclusive; reinforce transparency and accountability; strengthen protections against discrimination and harm; and clarify requirements and support operational needs.+ − Periodic reviews are not intended to be exhaustive. They seek to adapt the directive to pertinent trends in the Canadian and global AI landscape, while gradually refining the text of the instrument to support interpretation and facilitate compliance. The first review sought to clarify and reinforce existing policy requirements, update policy references, and strengthen transparency and quality assurance measures. The second review informed the development of guidelines supporting the interpretation of the directive.+ + + + + + + + + + + + + + + + + +
Third Review of the Directive on Automated Decision-Making (view source)
Revision as of 22:54, 24 August 2022
, 22:54, 24 August 2022→About the Third Review
== '''About the Third Review''' ==
== '''About the Third Review''' ==
=== Background ===
Treasury Board of Canada Secretariat (TBS) is completing the third review of the [https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32592 Directive on Automated Decision-Making]. The review takes stock of the current state of the directive and identifies risks and challenges to the government’s commitment to responsible artificial intelligence (AI) in the federal public sector. These issues highlight critical gaps that limit the directive’s relevance and effectiveness in supporting transparency, accountability, and fairness in automated decision-making. They also identify problems with terminology, feasibility, and coherence with other federal policy instruments.
Treasury Board of Canada Secretariat (TBS) is completing the third review of the [https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32592 Directive on Automated Decision-Making]. The review takes stock of the current state of the directive and identifies risks and challenges to the government’s commitment to responsible artificial intelligence (AI) in the federal public sector. These issues highlight critical gaps that limit the directive’s relevance and effectiveness in supporting transparency, accountability, and fairness in automated decision-making. They also identify problems with terminology, feasibility, and coherence with other federal policy instruments.
Periodic reviews are not intended to be exhaustive. They seek to adapt the directive to pertinent trends in the Canadian and global AI landscape, while gradually refining the text of the instrument to support interpretation and facilitate compliance. The first review sought to clarify and reinforce existing policy requirements, update policy references, and strengthen transparency and quality assurance measures. The second review informed the development of guidelines supporting the interpretation of the directive.
=== Policy recommendations ===
As part of the third review, TBS is proposing 12 policy recommendations and accompanying amendments to the directive:
# Expand the scope to cover internal services.
# Clarify that the scope includes systems which make assessments related to administrative decisions.
# Replace the 6-month review interval with a biennial review and enable the Chief Information Officer of Canada to request off-cycle reviews.
# Replace references to Canadians with more encompassing language such as clients and Canadian society.
# Introduce measures supporting the tracing, protection, and appropriate retention and disposition of data used and generated by a system.
# Expand the pre-production testing requirement to cover model bias testing.
# Mandate the completion of Gender Based Analysis Plus during the development of a system.
# Establish explanation criteria in support of the explanation requirement and integrate them into the Algorithmic Impact Assessment (AIA).
# Expand the AIA to include questions concerning an institution's reasons for pursuing automation.
# Mandate the publication of complete or summarized peer reviews and require completion prior to system production.
# Align the contingency requirement with relevant terminology established in Treasury Board security policy.
# Mandate the release of AIAs prior to the production of a system.
=== Expected outcomes ===
The recommendations would ensure that automated decision systems impacting federal public servants are fair and inclusive; reinforce transparency and accountability; strengthen protections against discrimination and harm; and clarify requirements; and support operational needs.
== '''Stakeholder Engagement''' ==
== '''Stakeholder Engagement''' ==
