AI conferences have a unique vibe.
They’re ostensibly tech events, featuring the requisite 30,000-foot view of the future and no roadmap on how to get there. But at this stage of the technology’s lifecycle, they’re also academic gatherings, and thus tend to feel a little insular and snooty… Like if OpenAI were a two-day event instead of a non-profit (for-profit?).
“How do we collect data so that we give it in the hands of the government in an efficient way? We’re in a democratic country. Isn’t this data supposed to inform the government?”
Which is why it was so refreshing to connect with Raesetje Sefala, currently a research fellow at The Distributed AI Research Institute (DAIR) and formerly a Mila researcher. Sefala has the data science chops but blends in a social science interest in human impacts: as she explains on the podcast, her origin story involves growing up in post-apartheid South Africa, looking around and wondering exactly what organizing principle her government was using to effect change.
It turns out it was more of a vibes thing, and through her work, Sefala has been both collecting and defining the data sets needed to first map her community and then chart its evolution. At ALL IN, she participated in a panel conversation on AI initiatives in Africa and what the Canadian ecosystem could learn from the work, and the takeaways are quite timely for a country with an abundance of bureaucracy and a noted lack of open data and civic tech.
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So, how is DAIR using computer vision, satellite imagery, and machine learning to understand the impacts of spatial apartheid in South Africa? How might Canadians learn from their work?
Let’s dig in.
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The BetaKit Podcast is hosted by Douglas Soltys & Rob Kenedi. Produced & edited by Jess Schmidt. Feature image courtesy DAIR.