🔬 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
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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
The Brief #156: AI Agents as the Next Disruptor – But Where’s the Governance?
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“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