Task Force on Machine Learning/AI


Machine learning is a transformative technology that has been widely adopted by various organizations. Applications in research libraries have been identified but adoption has been limited. While time, funding, and access to tools are common barriers to adoption, the lack of expertise or experience is often the first barrier identified.

To increase understanding and to help identify specific paths forward, this OCUL Director-level Task Force is taking the lead in identifying and organizing immediate next steps to provide an informed perspective on machine learning to allow OCUL to make strategic choices on utilizing and piloting aspects of this technology. Suggestions for immediate next steps include a position paper and a summit, with each informing the other. 


  • Mark Asberg (Queen's University)
  • Talia Chung (University of Ottawa)
  • Scott Gillies (Wilfrid Laurier University)
  • Vivian Lewis (McMaster University)
  • Mark Robertson (Toronto Metropolitan University)
  • Catherine Steeves (Western University)
  • Amy Greenberg (OCUL)
  • Kate Davis (Scholars Portal)
  • Michael Ridley 

This is a short-term group, expected to complete its work within six months with the possibility of a term extension to two years.

Task force established in October 2023