AI Ethics: Global Voices, Local Harm—The New Digital Colonialism In AI?

From military partnerships to underpaid labor in the Global South, the systems we deploy are built on global inequities. For the channel ecosystem and its leaders, AI ethics isn’t just about code—it’s about power.

In 2020, Dr. Timnit Gebru (pictured above), a prominent AI ethics researcher, was fired from Google. This was no ordinary firing—she was relieved of her duties after raising concerns about bias in large language models. Her critique centered on the disproportionate impact AI’s LLMs could have on marginalized communities. Her work was definitively critical of the LLMs she had a hand in building. And it is exactly the type of questioning we in the channel ecosystem need to continue.

Let’s put the AI policy challenges in context: The rapid growth of AI and the increased usage of LLMs require policies that are not only strategic, but inclusive. According the Boston Consulting Group, 74 percent of executives say AI is central to their growth strategies, yet only 15 percent have a dedicated AI ethics framework. The question becomes, why do less than a fourth of them have a dedicated AI framework?

One answer is a lack of psychological safety compounded by increasingly homogeneous teams. McKinsey data shows homogeneous teams are significantly more likely to overlook ethical red flags in product development. A lack of psychological safety makes it difficult for marginalized professionals to speak up, even when harm is evident. If you thought you’d be fired for calling out ethically gray areas, would you be like Dr. Gebru?

When Innovation Exploits Instead Of Includes

Without inclusive leaders who write AI policies, innovation risks becoming a new form of digital colonialism whereby data, labor and culture are extracted from marginalized communities without consent, compensation or proper representation.

Case in point: In 2023, Kenyan content moderators working for OpenAI were paid less than $2 per hour to review traumatic material used to train AI models.

Globally, the disparity is stark. Less than 1 percent of AI research funding goes to institutions in Africa, Latin America or Southeast Asia. Yet these communities in the Global South and beyond bear the brunt of AI’s hidden labor.

The result? AI systems that reflect the biases and values of the powerful, not those most impacted by their deployment.

The Military-Industrial-Tech Complex

Earlier this month, the U.S. Army swore in executives from Palantir, Meta and OpenAI as Army Reserve Lieutenant Colonels with no requirement of military experience or expertise. While the move was not completely unprecedented, it does solidify the links between tech sectors and global military power.

These companies already extract labor from the Global South and are now formally embedded within institutions that project force globally. This becomes a double extraction:

First, communities provide the invisible labor and data that fuel AI.
Then, those same systems are adapted for surveillance, targeting and geopolitical influence—all with limited accountability to the communities they originated from.

It echoes a familiar colonial pattern: Like the British East India Company, today’s tech giants fuse economic exploitation with military power. Only now, the resources are data, attention and human cognition rather than spices or land.

Digital Colonialism Is Here

And the channel ecosystem cannot afford to ignore it. As leaders in the tech channel, we do more than sell innovation; we shape how innovation impacts the world. Knowing this, we have a responsibility to ask hard questions about where our tools come from, who they serve and who is left out or harmed.

It’s not enough to focus on performance metrics or margin optimization if the systems we deploy are built on invisible labor, cultural erasure or structural inequity. While some see AI simply as a product to deploy, those of us committed to inclusive leadership structures see it as a reflection of our priorities, our partnerships and our values.

The next wave of growth in the channel will not come from technological innovation alone. It will come from deeper trust and shared accountability combined with ethical foresight. We have the power and collective responsibility to ensure that AI does more than scale profit. We have the ability to also do what is just.

So, the question stands: Will we be the architects of inclusive progress or silent partners in digital extraction?

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