The three literacies every Guyanese child needs

May 17, 2026 Features / Columnists, News

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By Dr. Karen Abrams, MBA. AA. 

(Kaieteur News) – How a child encounters artificial intelligence depends entirely on the teacher. In one classroom, it can feel intimidating, abstract, and disconnected from anything that matters in a young person’s life. In another, it can feel as natural and approachable as learning to read. The difference between those two classrooms is not the technology. It is the adult standing in front of the children.

Either way, every Guyanese student must develop AI literacy if they are to be competitive in the labour market they will actually enter, in this country or anywhere else in the world. The problem is that AI literacy cannot be built on a foundation that is not there. It rests on two prior literacies, and Guyana has been struggling with both.

Regular literacy first. Kaieteur News reported on 14 May 2026, citing a UNDP 2024 assessment, that the average Guyanese student now drops out of the school system midway through Grade Nine, around age fourteen. Children who leave school before completing secondary education will likely not develop AI literacy, will probably not develop digital literacy, and will probably not develop the foundation for any of the higher-order skills the next economy will demand.

The conversation about innovation in this country has to start there, with the basic fact that a system losing its students at fourteen cannot produce the workforce a competitive economy requires.  A Grade Nine dropout in 2025 could still find pathways into agricultural labour, construction, services, or trades that would support a household although they now face increasing competitive pressures from a new immigrant population.

However, a Grade Nine dropout in 2032 will face a labour market in which routine work has been automated and the floor for stable employment has risen sharply. The cost of the dropout crisis is not what it was twenty years ago. It is much higher, and it will keep rising. Defending regular literacy at the secondary level is therefore not a sentimental aspiration. It is the precondition for everything else this country wants to become. Digital literacy is the second foundation.

By this I mean not only the ability to operate a phone, which is now widespread, but the practical fluency to navigate computers, tablets, operating systems, browsers, email, learning platforms, files, folders, passwords, cloud storage, and the popular software that school, work, and business now require. Too many Guyanese students and adults can use WhatsApp, Facebook, and TikTok, but still struggle to attach a document, format a report, search responsibly, complete an online form, manage a spreadsheet, join a virtual class, protect a password, or troubleshoot a simple device problem. Consuming social media is not the digital literacy that really matters. Digital literacy means knowing how to use technology as a tool for learning, work, communication, production, and problem-solving. It also means understanding which information sources can be trusted, how to verify what is true, how to use productivity tools well, and how to participate as a creator rather than only as a consumer.

The information environment our students live in is now saturated with AI-generated content, synthetic media, deepfakes, and persuasive falsehoods produced at industrial scale. A child without the habit of asking who made this, why, and on what evidence will not navigate that environment safely, let alone productively. Without this layer, the AI literacy we want to build on top of it becomes either useless or actively dangerous. AI literacy itself sits on top. At STEMGuyana, we have tested different approaches with learners as young as nine. What we have found is that the chatbot, which is what most people associate with AI today, is the surface of a much deeper subject. The chatbot is subordinate to the actual understanding our students need to develop, which includes machine learning, the differences between supervised, unsupervised, and reinforcement learning, what a neural network is, what a large language model is, and how such models are trained.

Children at nine and ten are perfectly capable of grasping these concepts when they are taught with care and the right examples. What surprises them most, in our experience, is how much guesswork the systems actually do. Adults often assume AI is harder to teach than it is.

The children themselves move through the foundations quickly when the teacher explains the ideas honestly rather than mystifying them. More important than any single technical concept is one structural insight; AI systems are not deterministic. They are predictive. They produce probable outputs, not certain ones. Students who understand this also understand why their own credibility depends on verifying what AI tells them, why humans must remain in the loop on consequential decisions, and why getting useful work out of AI systems requires real skill in prompting, evaluating, and correcting the system rather than passive acceptance of whatever it generates.

The labour-market stakes of all this are not abstract. A Guyanese teenager entering the workforce in 2032 will face employers and clients who expect AI fluency as a baseline, in the same way computer literacy is now assumed.

Most jobs in services, administration, communications, design, analysis, and increasingly the trades will involve working alongside AI tools every day. The young people who are fluent in those tools, who can create and manage AI agents, implement APIs and other technologies will out-produce those who are not, by margins large enough to determine who is hired, who is promoted, and who is paid well. This is not a Caribbean problem alone. It is the global terrain on which our students will compete. The countries already addressing AI literacy in their school systems, including the United Kingdom, China, Estonia, Singapore, and the United Arab Emirates, are building national programmes from the primary level upward. Guyana cannot afford to watch.

But Warde and Sah, in their 2019 Creating a STEM-based Economic Pillar for the Caribbean, were right to insist on a deeper layer beyond fluency. The region needs not only AI users but AI builders. We need computer scientists who can design algorithms, train models, build neural networks, and architect systems. We will not train the frontier foundation models.

That work requires hundreds of millions of dollars in compute that small economies cannot deploy. But the applied layers of AI work, in agriculture, climate adaptation, healthcare, financial services, language tools, and creative industries, are entirely within reach. Caribbean engineers and scientists can build at those layers if the region creates the institutional conditions to support them. The economic literature on small economies, including the brain drain analysis by de la Croix and Docquier, is unambiguous about what happens to small states that fail to develop this layer. Their talented young people leave to build for someone else.

Three literacies, in this order. Regular literacy, defended against the dropout crisis. Digital literacy, taught with judgement and skill. AI literacy, built on the others rather than substituted for them. And beyond those three, the deeper layer of AI builders, scientists, and engineers who turn fluency into firms. Get this right, and Guyanese students can compete anywhere in the world. Get it wrong, and the most consequential decade in this country’s history will pass with another generation prepared for the economy of the past.

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• AI literacy, Artificial intelligence, Karen Abrams, literacies, STEMGuyana

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