The Alien in the Room: What AI Means for Education and Healthcare in Kenya

Reflections from a Kenyan international student, drawing on Ethan Mollick’s Co-Intelligence: Living and Working with AI and Our Next Reality, explored in Professor Greg Kessler’s Emerging Technology course at Ohio University

Last semester, I sat in Professor Greg Kessler’s Emerging Technology course at Ohio University and read two books back-to-back that genuinely unsettled me, in the best possible way. The first was Ethan Mollick’s Co-Intelligence: Living and Working With AI. The second was Our Next Reality, which painted an even broader canvas of where immersive and intelligent technologies are taking us. Together, they did something I did not expect they made me think constantly about home.

I came to Ohio University from Kenya, first completing my MA in International Studies and now pursuing a PhD in Instructional Technology. Those two degrees sit at an interesting crossroads, one trained me to think about global inequalities of power, resources, and opportunity; the other is training me to think about how technology can reshape learning. Reading Mollick in that context was not an academic exercise. It was personal.

There is a moment, Mollick writes, that comes after a few hours of really using an AI system, a moment where you stop thinking of it as a clever search engine and realize you are dealing with something genuinely new. Something that thinks, responds, and adapts in ways that no piece of software has ever done before. He calls it the cost of “really getting to know AI”, at least three sleepless nights. Kenya, as a country, is standing at the edge of those sleepless nights right now.

We talk a lot about AI as something happening elsewhere, in Silicon Valley, in Beijing, in the research labs of universities most Kenyans will never attend. But Mollick’s central argument is worth taking seriously from a Nairobi matatu, a rural dispensary in Turkana, or a public school in Kisumu: AI is not a niche technology. It is what scholars call a General-Purpose Technology, a once-in-a-generation shift, like the steam engine, like the internet, that touches every industry and every aspect of daily life. And crucially, unlike those earlier revolutions which largely replaced physical or repetitive work, this one target thinking. It augments, and in some cases replaces, human cognitive effort. That changes everything for a country where the most urgent development problems are about access to expertise.

The 2 Sigma Problem — and Kenya’s Version of It

In 1984, educational psychologist Benjamin Bloom published what became known as the “2 Sigma Problem.” He found that students who received one-on-one tutoring consistently performed two standard deviations better than students in a conventional classroom. In plain terms: the average tutored student scored higher than 98 percent of students in a regular class. The problem? Private tutoring is expensive, scarce, and simply out of reach for most families.

If you grew up in Kenya, you understand this problem intimately, not as research finding but as a lived reality. I grew up watching this gap up close. A student at a well-resourced private school in Karen or Lavington might have access to individual attention, specialist subject teachers, and exam prep coaching. A student at a public school in Mathare or Kitui is often sharing one underpaid teacher with sixty other children, in a classroom with no electricity, learning from a textbook that is five years out of date. It was that inequality, and a deep desire to understand how technology could bridge it, that eventually led me to Ohio University to study Instructional Technology.

AI does not fully solve this. Mollick is honest about that. But it creates something that has never existed before: a patient, tireless, personalized tutor that is available at any hour, in any subject, that will explain a concept fifty different ways until it clicks, and that is increasingly accessible on nothing more than a basic smartphone. Kenya already has some of the highest mobile phone penetration rates in Africa. The infrastructure for a tutoring revolution is already in Kenyan hands.

This matters enormously at a practical level. Imagine a Form Three student in Eldoret struggling with quadratic equations at 9pm, when their teacher has gone home and there is no one to ask. Today, they give up. Tomorrow, with AI as a co-intelligence, they type their question into a chat window and get a step-by-step explanation tailored to exactly where they got confused. Not a YouTube video they have to scrub through. Not a Google result they must decipher. A conversation. Mollick calls this the promise of finally solving the 2 Sigma Problem at scale, and for a country like Kenya, it is among the most significant promises AI makes.

The Homework Question (and Why It Is Not the Biggest Issue)

Mollick notes, with a touch of dark humour, that even before generative AI arrived, Kenya had a thriving industry of approximately 20,000 people writing academic essays full time for students overseas. AI did not introduce the cheating problem to Kenyan education; it accelerated a tension that was already there.

Reading that detail in Professor Kessler’s class, I almost laughed. Anyone who went through the Kenyan education system knows essay mills were not a secret. But Mollick’s point, and the conversation that Our Next Reality extends in its own way, is that the more important disruption is not about cheating. It is about what we teach and why. If AI can write a competent essay, summarize a textbook chapter, and solve most exam-style questions, then the purpose of education can no longer simply be content delivery. The real value of schooling shifts toward things AI cannot do: critical thinking, judgment, empathy, leadership, creativity rooted in lived experience. Kenyan educators and policymakers have an opportunity, right now to rethink curricula around these deeper skills, rather than defending assignments designed for a world that no longer exists.

My PhD training in Instructional Technology keeps bringing me back to this question: what does it mean to design learning for a world where AI is always in the room? The answer is not to ban it or to surrender to it. It is to be deliberate. The calculator was once feared in classrooms. By the 1990s it was standard. The same adjustment will happen with AI. The question is whether Kenya’s education system shapes that transition deliberately or is shaped by it.

The Doctor who is Never off Duty

 

Kenya has roughly one doctor for every ten thousand people. The World Health Organization recommends one per thousand. That gap, nine thousand people per available doctor, is not a statistic. It is a child in Garissa who waits weeks for a diagnosis. It is a mother in Migori who gives birth without skilled attendance. It is a community health volunteer in Baringo who knows something is wrong with a patient but does not have the training to name it.

This is where Mollick’s framing of AI as co-intelligence becomes most powerful in the healthcare context. He describes AI not as a replacement for experts, but as something that brings expert-level capability to people who would otherwise never have access to it. Studies he cites show AI improving productivity in professional tasks by 20 to 80 percent, and critically, the gains are largest for people who are least experienced, because AI levels the playing field upward. A junior community health worker supported by an AI diagnostic tool is not a replacement for a doctor. But they are dramatically more capable than a community health worker working alone.

This is not hypothetical. AI tools can already screen chest X-rays for tuberculosis with accuracy comparable to radiologists. They can analyze skin conditions from a photograph. They can triage symptoms, flag drug interactions, and surface relevant clinical guidelines in Swahili. These are not luxuries for a well-resourced hospital in Wetlands. They are survival tools for a dispensary in Wajir where the nearest specialist is four hours away.

Kenya’s network of community health promoters, one of the largest and most organized in Africa, represents an incredible distribution channel for AI-augmented healthcare. Training those workers to use AI as a diagnostic co-intelligence could extend the effective reach of Kenya’s medical system without waiting for the country to train thousands more doctors it currently cannot afford.

Mollick does not write a utopian book, and this blog should not be a utopian piece. Neither does Our Next Reality, which pushed our class discussions in Professor Kessler’s course toward harder questions about who controls these technologies, who benefits, and who gets left behind when the next wave of immersive and intelligent tools arrives.

The same AI that could personalize education for a child in Kibera could also flood social media with health misinformation in Kiswahili. The same tool that could help a community health worker in Turkana could widen the gap between those with reliable internet access and those without. AI will not automatically serve those who need it most, it will serve those who have the infrastructure, the literacy, and the policy environment to use it well.

My background in International Studies trained me to be suspicious of technologies that promise to “leapfrog” development without asking whose interests they serve. The mobile money revolution with M-Pesa was extraordinary, but it happened because Kenya built the right conditions for it. The same intentionality is required now. This is the challenge for Kenya’s government, its tech community, and its civil society: to approach AI not as passive recipients of technology built for other markets, but as active co-designers of how it gets deployed here. That means investing in digital infrastructure in underserved counties, developing AI tools grounded in local languages and contexts, and building the regulatory capacity to manage risks before they become crises.

Three Sleepless Nights

Mollick ends his introduction with a simple observation: we are all going to have our three sleepless nights with AI. The question is not whether the technology will arrive in Kenya, it already has. The question is what we do with the excitement and the unease of those nights.

I had my sleepless nights in Professor Kessler’s class in Athens, Ohio, thousands of miles from Nairobi. I read these books as a Kenyan living the strange double life of an international student, absorbing ideas from a well-resourced American university while thinking about classrooms back home that lack textbooks, and dispensaries that lack doctors. That distance is uncomfortable. But it is also clarifying. It made me see, with unusual sharpness, what these technologies could mean for a place that has more to gain from them than almost anywhere else on earth.

For a country where the greatest inequalities are inequalities of access, access to quality teachers, to qualified doctors, to expert guidance of any kind, AI offers something genuinely extraordinary: the possibility of bringing world-class co-intelligence within reach of every Kenyan student, every rural health worker, every first-generation university student trying to figure out the world without a roadmap.

That possibility is worth losing a little sleep over.

Collins Ketere is a Kenyan international student at Ohio University, where he completed an MA in International Studies and is currently pursuing a PhD in Instructional Technology. This piece was written in the spirit of ideas explored in Professor Greg Kessler’s Emerging Technology course, where Ethan Mollick’s Co-Intelligence: Living and Working with AI (Portfolio/Penguin, 2024) was paired with Our Next Reality as companion readings.