Inclusion lessons from the indigenous data movement
When we're talking about machine learning, AI and conservation, we're talking about digitizing land into shapes, taking imagery and turning it into shapes, and then designating uses for that shape on the land surface.
We are essentially digitizing trees, animals, and plants and rivers, and boundaries, defining those using satellite imagery.
Therefore there are ethical considerations when it comes to indigenous rights because of the way indigenous people connect and identify to land and natural resources. When you digitize, you have classified and defined lands and territories. Usually, the decisions on how to utilize those lands and natural resources don’t include engaging with the indigenous communities who are living on that land. And so regardless of if you've gone through the ethical processes and evaluated all of those responsible aspects around how imagery is used and the algorithms that are produced. How does that affect both collective and personal digital identity in the future given how Indigenous people identify with nature?
How do you define collectivized knowledge and collectivize that identity as a people, rather than the Western-centric, individualistic person? These sorts of concepts aren't currently being discussed and defined in the mainstream.
However, groups are emerging that discuss how to centre the concerns of indigenous peoples in the design process: https://www.indigenous-ai.net/position-paper/