
Rethinking AI from the Ground Up: Lessons from EACL 2026
What if the biggest limitation in today’s AI systems isn’t the model, but the quality of the data we feed into it?

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What if the biggest limitation in today’s AI systems isn’t the model, but the quality of the data we feed into it?


Participatory and scalable methods to ensure AI tools in healthcare are evaluated not just on performance, but on real-world impact.


From a Jupyter notebook prototype to a production-ready RAG system: the engineering journey behind our internal AI assistant.


How AI and voice technology are revolutionizing access to health information across diverse African linguistic landscapes.


An exploration of the representation gap in major LLMs and why "Western" AI often hallucinates when asked about African contexts.


How we engaged young people to design a safe, non-judgmental AI companion for sensitive health discussions.


Why Human-Centered Design is the key to building AI tools that are not just smart, but culturally safe and relevant.
