🔬 Research Summary by Caner Hazirbas, Research Scientist at Meta and Ph.D. graduate in Computer Vision from the Technical University of Munich. [Original paper by Caner Hazirbas, Alicia Sun, Yonathan Efroni, Mark … [Read more...] about The Bias of Harmful Label Associations in Vision-Language Models
Special Topics
AI Governance on the Ground: Canada’s Algorithmic Impact Assessment Process and Algorithm has evolved
✍️ Report Summary by Kate Kaye, a researcher, award-winning journalist and deputy director of the World Privacy Forum, a non-partisan public interest research 501c3 nonprofit organization. Kate is a member of the OECD.AI … [Read more...] about AI Governance on the Ground: Canada’s Algorithmic Impact Assessment Process and Algorithm has evolved
Self-Improving Diffusion Models with Synthetic Data
🔬 Research Summary by Sina Alemohammad, a PhD candidate at Rice University with a focus on the interaction between generative models and synthetic data. [Original paper by Sina Alemohammad, Ahmed Imtiaz Humayun, … [Read more...] about Self-Improving Diffusion Models with Synthetic Data
“Made by Humans” Still Matters
✍️ By Jim Huang, Solutions Director and AI Ethics Researcher, and Abhishek Gupta, Founder and Principal Researcher, Montreal AI Ethics Institute. Editor’s Note: This article, ‘“Made by Humans” Still Matters’ was … [Read more...] about “Made by Humans” Still Matters
The Death of Canada’s Artificial Intelligence and Data Act: What Happened, and What’s Next for AI Regulation in Canada?
✍️ Op-Ed by Blair Attard-Frost, a PhD Candidate at the University of Toronto. She researches and teaches about the governance of AI systems in Canada and globally. Summary Canada is currently experiencing a … [Read more...] about The Death of Canada’s Artificial Intelligence and Data Act: What Happened, and What’s Next for AI Regulation in Canada?