Algorithmic Impact Assessment (AIA) - Leveraging Artificial Intelligence (AI) for backlog reduction: AI assistant prototype

Algorithmic Impact Assessment (AIA) - Leveraging Artificial Intelligence (AI) for backlog reduction: AI assistant prototype PSPC Human Capital Management aims to address and eliminate the existing backlog of pay cases by implementing an AI assistant designed to support compensation agents (CA). The primary objective of the AI assistant is to offer advice and necessary information to CAs and support them in expediating case closure. Currently, the tool is applied to synthetic data on select case types (actings) that are over 365 days old. Adopting a hybrid-by-design approach, this initiative aims to harness the strengths of both human insight and machine efficiency. This approach enables rapid data consumption and recommendations by machines, while CAs retain decision-making authority over how the data is used, ensuring a balanced and effective resolution process. The project will focus on aggregating relevant case data and information, assessing it for accuracy and completeness, and validating it against authoritative sources such as approved standard operating procedures (SoPs), job aids, directives, and policy documents. This comprehensive strategy aims to enhance the efficiency and accuracy of CAs work, facilitate faster case resolutions, and elevate the quality of service. ___________________________________ Details of AIA releases: April 2024, Version 1: testing with synthetic data began August 2024, Version 2: testing with production data began 2024-09-05 Public Services and Procurement Canada open-ouvert@tbs-sct.gc.ca Information and CommunicationsLabourPersonsScience and TechnologyAlgorithmic Impact AssessmentAIAAIArtificial Intelligence AIA v1 (PDF file, in English)PDF https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-eng-v1.pdf AIA v1 (PDF file, in French)PDF https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-fra-v1.pdf AIA v1 (HTML of the PDF file, in English)HTML https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-eng-v1.html AIA v1 (HTML of the PDF file, in French)HTML https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-fra-v1.html AIA v1 (bilingual JSON file)JSON https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-v1.json AIA v2 (PDF file, in English)PDF https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-eng-v2-2.pdf AIA v2 (PDF file, in French)PDF https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-fra-v2-2.pdf AIA v2 (HTML of the PDF file, in English)HTML https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-eng-v2-2.html AIA v2 (HTML of the PDF file, in French)HTML https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-fra-v2-2.html AIA v2 (bilingual JSON file)JSON https://donnees-data.tpsgc-pwgsc.gc.ca/bh1/eiaia-aiaai/eia-ia_aia-ai-v2-2.json

PSPC Human Capital Management aims to address and eliminate the existing backlog of pay cases by implementing an AI assistant designed to support compensation agents (CA). The primary objective of the AI assistant is to offer advice and necessary information to CAs and support them in expediating case closure. Currently, the tool is applied to synthetic data on select case types (actings) that are over 365 days old.

Adopting a hybrid-by-design approach, this initiative aims to harness the strengths of both human insight and machine efficiency. This approach enables rapid data consumption and recommendations by machines, while CAs retain decision-making authority over how the data is used, ensuring a balanced and effective resolution process.

The project will focus on aggregating relevant case data and information, assessing it for accuracy and completeness, and validating it against authoritative sources such as approved standard operating procedures (SoPs), job aids, directives, and policy documents. This comprehensive strategy aims to enhance the efficiency and accuracy of CAs work, facilitate faster case resolutions, and elevate the quality of service.

Details of AIA releases:

April 2024, Version 1: testing with synthetic data began

August 2024, Version 2: testing with production data began

Data and Resources

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