In Part Two, we move on to Venezuela, where AI data-labeling firms find cheap and desperate workers amid a devastating economic crisis, creating a new model of labor exploitation. The series also looks at ways to get away from this dynamic. In the third part, we visit ride-hauling drivers in Indonesia who are learning to resist algorithmic control and fragmentation by building power through the community. In the fourth part, we end New Zealand’s Mરીori name in Aoteroa, where an indigenous couple regains control of their community’s data to revive their language.
Together, the stories show how AI is impoverishing communities and countries that have no say in its development – the same communities and countries that are already impoverished by former colonial empires. They also suggest how AI could be so much more – a way for historically disadvantaged people to restore their culture, their voice and their right to determine their own future.
Ultimately the purpose of this series is: to broaden the perspective on the impact of AI on society so that one can begin to explore how things can be different. It is not possible to talk about “AI for everyone” (Google’s rhetoric), “Responsible AI” (Facebook’s rhetoric) or “Largely distributed”[ing]Without honestly acknowledging its advantages (OpenAI’s rhetoric) and facing obstacles along the way.
Now a new generation of scholars is championing “decolonial AI” to restore power from the Global North to the Global South, from Silicon Valley to the people. I hope this series can provide a prompt for what “decolonial AI” might look like – and an invitation, as there is so much to explore.