Training the Next Generation of Indigenous Data Scientists

“Native DNA is so sought after that people are looking for proxy data, one of the big proxy data is the microbiome” Mr. Yracheta said. “If you’re a Native person, you have to consider all these variables if you want to protect your people your culture.”

In a presentation at the conference, Joslynn Lee, a member of the Navajo, Laguna Pueblo Acoma Pueblo Nations a biochemist at Fort Lewis College in Durango, Colo., spoke about her experience tracking the changes in microbial communities in rivers that experienced a mine wastewater spill in Silverton, Colo. Dr. Lee also offered practical tips on how to plan a microbiome analysis, from collecting a sample to processing it.

In a data-science career panel, Rebecca Pollet, a biochemist a member of the Cherokee Nation, noted how many mainstream pharmaceutical drugs were developed based on the traditional knowledge plant medicine of Native people. The anti-malarial drug quinine, for example, was developed from the bark of a species of Cinchona trees, which the Quechua people historically used as medicine. Dr. Pollet, who studies the effects of pharmaceutical drugs traditional food on the gut microbiome, asked: “How do we honor that traditional knowledge make up for what’s been covered up?”

One participant, the Lakota elder Les Ducheneaux, added that he believed that medicine derived from traditional knowledge wrongly removed the prayers rituals that would traditionally accompany the treatment, rendering the medicine less effective. “You constantly have to weigh the scientific part of medicine with the cultural spiritual part of what you’re doing,” he said.

Over the course of the IndigiData conference, participants also discussed ways to take charge of their own data to serve their communities.

Mason Grimshaw, a data scientist a board member of Indigenous in A.I., talked about his research with language data on the International Wakashan A.I. Consortium. The consortium, led by an engineer, Michael Running Wolf, is developing an automatic speech recognition A.I. for Wakashan languages, a family of endangered languages spoken among several First Nations communities. The researchers believe automatic speech recognition models can preserve fluency in Wakashan languages revitalize their use by future generations.

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