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CAN/DGSI 128, Machine Learning and AI Implementation in Research Institutions (D4)

Technical Committee Review

This document specifies minimum requirements for implementing machine learning (ML) and artificial intelligence (AI) systems within Canadian research institutions including libraries, archives, research centres, labs, universities, colleges and/or CEGEPs and other institutions that conduct or support research. This list is not exhaustive; any institution, large or small, that determines its work falls under the scope and vulnerabilities described in this standard is encouraged to adopt it.

This document does not refer to the actual development of frontier models or advanced AI. However, the practices and guidance outlined here may be useful in supporting a more in-depth standard or policy for AI governance in frontier model or private AI development contexts.

Within the broader scope of this document there are two sub-sections to be examined:

  1. Operational Use: Use of AI in the internal systems of research institutions that collect, handle, store, preserve, and disseminate data supporting various research tasks.
  2. Research Use: Use of AI tools in the analysis and/or collection and/or preparation of data for research purposes.

DATE POSTED: December 11th, 2024

DEADLINE FOR COMMENTS: January 31st, 2025

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Maureen Dec 11 2024 at 12:56PM on page 16

Editorial
I am wondering if we could add guidance here by linking the OCAP Principles and the CIHI Guidance on the Use of Standards
for Race-Based and Indigenous Identity Data Collection and
Health Reporting in Canada, directly below? Similar to the "refer to guidance" part in the section below (6.2.2.1). I worry that people may need more information and examples to really understand this section on Data Sovereignty, and it is very important, given the long history of misuse of Indigenous data in Canada.
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Kingston Dec 11 2024 at 9:26AM on page 15

Technical
Is this always possible? Are there 'reasonable' limits to what data sets need to be prioritized? I would assume there are a number of institutional projects that aggregate corpus that could quickly overwhelm secure storage?
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