Using artificial intelligence (AI) to automate candidate evaluations in the staffing process's assessment phase
Using artificial intelligence (AI) to automate candidate evaluations in the staffing process's assessment phase is an open dataset from Treasury Board of Canada Secretariat with 3 files (PDF, JSON); catalogue record updated 2024-11-21. On CanQuery you can follow the original downloads. Files are available in English and French.
Detailed results from the Algorithmic Impact Assessment (AIA) for the Knockri pilot project. The goal of the proposed pilot project is to reduce the time and cost associated with conducting interviews, resolve potential issues with rater bias, and maintain a high degree of structure and rigor in the interview process. Providing all candidates with equal opportunity for employment within the Canadian government.
- Publisher
- Treasury Board of Canada Secretariat
- Resources
- 3
- Catalogue metadata updated
- 2024-11-21
Data overview
- Formats
- JSON, PDF
- File languages
- English, French
Official sources and licences
Resources
- Algorithmic Impact Assessment - Using artificial intelligence (AI) to automate candidate evaluations in the staffing process's assessment phase (French, PDF) PDF · Download PDF
- Algorithmic Impact Assessment - Using artificial intelligence (AI) to automate candidate evaluations in the staffing process's assessment phase (English, French, JSON) JSON · Download JSON
- Algorithmic Impact Assessment - Using artificial intelligence (AI) to automate candidate evaluations in the staffing process's assessment phase (English, PDF) PDF · Download PDF