Canada's national artificial intelligence governance system: Dataset from interviews with 20 government leaders & subject matter experts

Summary

Anonymized aggregate data from interviews with 20 government leaders and subject matter experts. The data was collected as part of a study of Canada's national system of artificial intelligence governance. The data was collected from February 2023 to July 2023. The dataset contains 610 topics that emerged from thematic analysis of interview transcripts from July 2023 to October 2023. The contexts, actors, resources, networks, evaluations, logics, functional bounds, rules, ecosystem-level dynamics, opportunities for improvement, and other topics contained in the dataset collectively represent the most significant components of Canada's national AI governance system that emerged over the course of the interviews with the 20 participants.

Notes for interpreting this dataset

Topics in analytical dimensions 1, 3, and 6-11 contain counts of the frequency with which aggregate topics emerged across each of the interviews with the 20 participants. Topics in analytical dimensions 2, 4, and 5 contain categories instead of frequency counts: the topics in these dimensions represent every unique actor, resource, and network that emerged over the course of the interviews instead of aggregate topics. 

Column titles contain the following abbreviations:
LEAD: Interviews with leaders of public sector AI governance initiatives.
SME-PS: Interviews with subject matter experts employed in the private sector.
SME-CS: Interviews with subject matter experts employed in the academic or civil sectors.

Full report

A report containing more information about this dataset and about the findings of our study can be found on SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4783525