Afaf Taïk
Université de Sherbrooke & MilaAbout
the speaker
Dr. Afaf Taïk is an assistant professor at the Université de Sherbrooke and currently a postdoctoral researcher at Mila – Quebec AI Institute and the Université de Montréal, working on the intersection of fairness and privacy in machine learning.
The cost of one-solution-fits-all models
This talk examines how the shift from highly customizable, small-scale machine learning systems to large, reusable models changes the AI landscape. As development moves toward off-the-shelf systems, the wide space of possible models narrows, and AI systems begin to look and behave more alike across contexts. The talk then asks what is gained and lost through this homogenization, and how responsibility should be understood when key design choices are no longer made locally, but embedded in widely deployed models.