Series by Karen Hao: “…Over the last few years, an increasing number of scholars have argued that the impact of AI is repeating the patterns of colonial history. European colonialism, they say, was characterized by the violent capture of land, extraction of resources, and exploitation of people—for example, through slavery—for the economic enrichment of the conquering country. While it would diminish the depth of past traumas to say the AI industry is repeating this violence today, it is now using other, more insidious means to enrich the wealthy and powerful at the great expense of the poor….
MIT Technology Review’s new AI Colonialism series, which will be publishing throughout this week, digs into these and other parallels between AI development and the colonial past by examining communities that have been profoundly changed by the technology. In part one, we head to South Africa, where AI surveillance tools, built on the extraction of people’s behaviors and faces, are re-entrenching racial hierarchies and fueling a digital apartheid.
In part two, we head to Venezuela, where AI data-labeling firms found cheap and desperate workers amid a devastating economic crisis, creating a new model of labor exploitation. The series also looks at ways to move away from these dynamics. In part three, we visit ride-hailing drivers in Indonesia who, by building power through community, are learning to resist algorithmic control and fragmentation. In part four, we end in Aotearoa, the Maori name for New Zealand, where an Indigenous couple are wresting back control of their community’s data to revitalize its language.
Together, the stories reveal how AI is impoverishing the communities and countries that don’t have a say in its development—the same communities and countries already impoverished by former colonial empires. They also suggest how AI could be so much more—a way for the historically dispossessed to reassert their culture, their voice, and their right to determine their own future.
That is ultimately the aim of this series: to broaden the view of AI’s impact on society so as to begin to figure out how things could be different. It’s not possible to talk about “AI for everyone” (Google’s rhetoric), “responsible AI” (Facebook’s rhetoric), or “broadly distribut[ing]” its benefits (OpenAI’s rhetoric) without honestly acknowledging and confronting the obstacles in the way….(More)”.