In the same way, the paper’s authors argue, this colonial history explains some of the most troubling characteristics and impacts of AI. They identify five manifestations of coloniality in the field:

Algorithmic discrimination and oppression. The ties between algorithmic discrimination and colonial racism are perhaps the most obvious: algorithms built to automate procedures and trained on data within a racially unjust society end up replicating those racist outcomes in their results. But much of the scholarship on this type of harm from AI focuses on examples in the US. Examining it in the context of coloniality allows for a global perspective: America isn’t the only place with social inequities. “There are always groups that are identified and subjected,” Isaac says.

Ghost work. The phenomenon of ghost work, the invisible data labor required to support AI innovation, neatly extends the historical economic relationship between…

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