The Parallel World of AI and Colonization
Before Artificial Intelligence automated the art of the grand theft, humanity thoroughly enjoyed its own analog golden age of plagiarism and global looting. It remains a favorite historical pastime: either an individual pinches another's craftsmanship to claim unearned authorship or a grand empire pillages entire cultural treasures just to display them in metropolitan museums like glittering war trophies.
Let’s focus on the looting. Artificial Intelligence is fundamentally engineered on this exact imperial blueprint: heist everyone’s intellectual property, then masquerade as an innocent, algorithmically objective machine merely executing developer orders. It’s impossible to ignore the imperial footprints of colonization stamped all over this “naïve” tool as it aggressively scrapes every byte of data across the open internet.
Indeed, the machine digitalizes the classic plunder perfected by the British, French, Spanish, German, Dutch, and Belgian empires across Africa, the Americas, and Asia, the entire globe, to be precise. Even the United States, that relatively young geopolitical upstart turned global policeman, has mastered this digital extraction. One must recognize the unmistakable hallmarks of colonization, even when they manifest in the metaverse.
The only real difference lies in the corporate branding of the players on the board. Where we once had maritime empires deploying pirate-looking ships to drop anchor, slaughter locals, and claim sovereign lands in the name of King and God, leaving behind centuries of carnage, slavery, and resource depletion, we now have Big Tech conglomerates quietly conquering the globe. They train their Large Language Models by force-feeding them digital artifacts, copyrighted literature, and every scrap of public data available, all without paying a single dime to the actual creators. The resulting astronomical profits are pocketed by tech CEOs who proudly flaunt soaring charts on-screen as their market capitalizations cross the multi-trillion-dollar threshold. A quick mathematical calculation reveals that Silicon Valley and old-school imperial colonization are perfectly synchronized in their commitment to grand larceny.
Moreover, this digital colonization enforces absolute linguistic hegemony. Just as historic colonies were forced to adopt the language of their conquerors (ironically, this very critique is written in an imperial tongue), modern LLMs replicate this cultural bias through their default architecture: English syntax and strictly Western logic (now available in your own imperial tongue). Query ChatGPT or Gemini about indigenous traditions, and the chatbot will inevitably view them through a Eurocentric lens unless you interrogate it with exhaustive precision. The structural bias is baked in. But while tech giants claim the algorithm magically trains itself, we must ask: who is actually doing the dirty work?
Naturally, AI monopolies exploit cheap, outsourced labor in the Global South to sanitize and calibrate their models for global consumption. Just like historical empires, they have engineered an extractive labor ecosystem to maximize profit margins at the absolute lowest cost, though back then, it was called the barbaric business of human slavery. To note a subtle point of modern differentiation: today's tech companies at least toss a few pennies at their digital sweatshop workers to keep the data pipelines flowing. Let's not forget, these AI chatbots aren't conscious; they feel no guilt because they aren't even alive.
A final parallel between digital conquest and historic colonization lies in their shared obsession with labeling and categorization. Because these models are forged almost exclusively within a Westernized cultural crucible, critical data frameworks, such as facial recognition, automated hiring algorithms, or predictive credit scoring, are inherently conditioned by biased training datasets. Consequently, they systematically recreate stereotypes and cultural prejudices reminiscent of historical caste systems or racial hierarchies. For the marginalized individual awaiting an automated, high-stakes systemic decision, the outcome mirrors history perfectly: systematic rejection, digital discrimination, and algorithmic exile.
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