"Sometimes, carrying on, just carrying on, is the superhuman achievement."

One of the more remarkable things I’ve read on the experience of working with AI, and one that matches personal experience

via @C_Hendrick

“The more sophisticated an automated system becomes, the more demanding, not less, the human role within it…”

— Jonathan Libov (@libovness) March 14, 2026

Indeed, we who work under mandates to use these tools - and evangelize their use - can feel pretty overwhelmed by it all.  Let us also not forget the hidden laborers who make this supposed Easy Button function:

Data labelers train, refine, and moderate the outputs of AI tools made by the largest companies in the world, yet they are wildly underpaid and haven’t benefitted from the runaway valuations of AI companies... 

These workers are required to stare at horrific content for many hours straight with few mental health resources, are largely managed by opaque algorithms, and, crucially, are the workers powering the runaway valuations of some of the richest and most powerful companies in the world... 

“When you think of colonialism, we were under British Imperial East Africa Company […] so literally, we are working under a company. We are just products, part of their operation. Stakeholders, we can say, but we are at the bottom of the bottom.”

“These multinationals are coming to rule and dominate here,” [Angela] added. “It’s a very unfortunate supply chain, and my call today as data labelers is to build up on this—as we are fighting for labor rights, we are also fighting for the environment […] we are fighting big companies. We are fighting the British imperialist companies of today. It’s Apple, it’s Meta, it’s Gemini. Those are the ones we’re still fighting. It’s a call for solidarity and expanding our thinking beyond what we are doing, beyond our labor.” 

In my few days in Kenya earlier this year, where I was traveling to speak at a conference about AI and journalism, it was immediately clear that data labelers make up a significant portion of the country’s tech workforce. 

Nearly everyone I spoke to there had either been a data labeler (or a content moderator) themselves or knows someone who has. Leaving the airport in Nairobi, you immediately drive by Sameer Business Park, an office complex that houses Sama, a San Francisco-headquartered “data annotation and labeling company” that has contracted with Meta, OpenAI, and many other tech giants. Sama has been sued repeatedly for its low pay and the fact that many of its workers suffer PTSD from repetitively looking at graphic content. 

For years, a giant sign outside its office read: “Samasource THE SOUL OF AI.” My Uber driver asked why I was going to a random office building in Nairobi’s Central Business District—I told her I was going to interview a data labeler. “Oh, I do data labeling too,” she said.

These are the people who describe the world to those vaunted LLMs that compute probabilities to generate AI slop for us.  We must always feed the machine:

Selah.