Education-centered critical policy analysis of AI: Ghana's AI strategy as a case
This study employs a critical qualitative analysis of Ghana's National Artificial Intelligence Strategy (2025-2035) to reveal that while the policy ambitiously addresses national workforce readiness and inclusion, it critically lacks a detailed, education-centered framework for school-level implementation, teacher preparation, curriculum reform, and learner protection.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Governments around the world are writing new plans to guide how artificial intelligence will shape their countries. These plans, often called national strategies, are like roadmaps for the future. They decide where to invest money, how to train workers, and what rules to follow. For many nations, a major part of this plan is education. The idea is that schools must prepare young people to work with these new tools. However, there is a growing question about what that preparation actually looks like. Does it mean teaching students to build the technology, or does it mean teaching them how to live and learn alongside it? This distinction matters because schools are not just factories for future workers; they are places where children learn to think, understand their culture, and interact with each other. When a government writes a policy for artificial intelligence, it must decide if it is treating education as a pipeline for jobs or as a complex system that needs its own careful rules for safety, fairness, and teaching.
A team of researchers from Ghana and international institutions decided to look closely at Ghana's own national plan. They examined the country's National Artificial Intelligence Strategy, a document meant to guide the nation from 2025 to 2035. The researchers wanted to see if this plan truly understood the daily reality of a classroom. They did not just read the document to see what it said about technology; they analyzed it to see how it treated teachers, students, and the specific challenges of learning in a place with many different languages and cultures. They used a new way of looking at policy, one that asks whether the plan supports the actual work of teaching and learning, or if it only focuses on making the country competitive in the global economy.
The researchers found that the Ghanaian strategy is ambitious and forward-thinking in many ways. It sets a clear goal to train over one million young people in artificial intelligence skills by the year 2033. It recognizes that the country needs to build a workforce that can participate in the digital economy. The plan also shows a strong commitment to inclusion, promising to bring training to rural areas, to women, and to people with disabilities. It even acknowledges the importance of using local languages to build better technology, noting that most current systems only understand English. These are significant steps for a nation that has historically faced barriers in adopting new technologies. The plan correctly identifies that for Ghana to succeed, it must not just import tools from other countries but develop its own capacity.
However, the analysis revealed a significant gap between the big national goals and the small, daily realities of a school. While the plan speaks loudly about training "AI-ready youth," it says very little about how a teacher should actually use these tools in a classroom. The document focuses heavily on the end result—producing skilled workers—but skips over the journey of how to teach them. For instance, the plan suggests updating school curriculums to include coding and data science, but it does not explain how a teacher in a primary school should introduce these ideas to a seven-year-old. It does not offer a step-by-step guide for how these lessons should grow as a child gets older. The plan treats teachers mostly as people who need to be trained to use new software, rather than as professional experts who need to make complex decisions about how to protect students and adapt lessons to their specific community.
The researchers also pointed out that the plan is quiet on the most difficult parts of using artificial intelligence in schools. It does not provide clear rules for students on when they can use AI to help with homework or when it counts as academic dishonesty. In a country where exams are a major part of education, the lack of guidance on how to grade work that might have been helped by a computer creates confusion. The plan also misses the chance to explain how to teach in a way that respects local cultures. Ghana has many different languages and cultural traditions. The researchers noted that while the plan mentions collecting data in local languages to build better computers, it does not explain how to use those languages to help children understand difficult concepts in the classroom. It treats language as a technical resource for machines, rather than a vital tool for human learning and connection.
Another striking finding was about the people who were missing from the conversation. The strategy document lists many government agencies, technology companies, and universities as key partners. Yet, the people who actually run schools—teachers, school leaders, parents, and the students themselves—are barely visible in the plan. The researchers argued that this is a problem because these are the people who will have to make the plan work every day. If the people who know the most about the challenges of rural schools or the needs of children with disabilities are not part of designing the policy, the plan may look good on paper but fail in practice. The researchers suggested that for the plan to succeed, the government needs to invite these groups to the table to help shape the rules, not just follow them.
The study also noticed something unusual about the document itself. The researchers found that the strategy included images that looked like they were created by artificial intelligence, but the document did not say so. This seemed to contradict the plan's own advice about being honest and transparent when using AI. If a government document is asking schools to be clear about how they use technology, it should model that same honesty in its own writing. This small detail highlighted a larger issue: the plan talks about responsible use of technology, but it does not always practice what it preaches in its own presentation.
Ultimately, the researchers concluded that Ghana has a strong foundation for its future, but it needs to build a more detailed bridge between its national goals and its classrooms. The plan is excellent at setting a vision for the country's economy and workforce, but it needs a companion plan specifically for education. This new plan would need to focus on the teacher, the student, and the specific cultural context of Ghana. It would need to answer questions like: How do we teach ethics in a local language? How do we protect a child's privacy when they use a learning app? How do we ensure that a student in a village with poor internet gets the same opportunities as a student in the city? The researchers believe that if Ghana can develop this education-centered approach, involving teachers and communities in the process, the country can create a future where artificial intelligence helps everyone learn, rather than just preparing a few for a job. The technology is ready, but the human side of the equation still needs more work.
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