Partly two, we head to Venezuela, the place AI data-labeling corporations discovered low-cost and determined employees amid a devastating financial disaster, creating a brand new mannequin of labor exploitation. The sequence additionally seems at methods to maneuver away from these dynamics. Partly three, we go to ride-hailing drivers in Indonesia who, by constructing energy by means of group, are studying to withstand algorithmic management and fragmentation. Partly 4, we finish in Aotearoa, the Maori title for New Zealand, the place an Indigenous couple are wresting again management of their group’s information to revitalize its language.
Collectively, the tales reveal how AI is impoverishing the communities and nations that don’t have a say in its improvement—the identical communities and nations already impoverished by former colonial empires. Additionally they recommend how AI might be a lot extra—a approach for the traditionally dispossessed to reassert their tradition, their voice, and their proper to find out their very own future.
That’s finally the intention of this sequence: to broaden the view of AI’s affect on society in order to start to determine how issues might be completely different. It’s not doable to speak about “AI for everyone” (Google’s rhetoric), “responsible AI” (Fb’s rhetoric), or “broadly distribut[ing]” its advantages (OpenAI’s rhetoric) with out actually acknowledging and confronting the obstacles in the best way.
Now a new generation of scholars is championing a “decolonial AI” to return energy from the International North again to the International South, from Silicon Valley again to the folks. My hope is that this sequence can present a immediate for what “decolonial AI” would possibly seem like—and an invite, as a result of there’s a lot extra to discover.