Category: MIL-OSI

Source: The Conversation – Africa – By Abiodun Olusola Omotayo, Ass. Professor, University of Maryland Eastern Shore; North-West University

Globally, agriculture faces mounting pressures. These are driven by climate change, land degradation, labour shortages, supply chain disruptions and the demand for food from a growing population.

At the same time, productivity is uneven. For example, maize yields in the US often exceed 10 tons per hectare. These high yields are driven by mechanisation, improved seed varieties, irrigation and efficient input use, supported increasingly by precision agriculture technologies. In contrast, yields in many parts of sub-Saharan Africa remain around 2-3 tons per hectare. This reflects constraints like limited access to inputs, reliance on rain-fed systems and weaker infrastructure and institutional support.

Smallholder farmers make up around 80% of farmers in developing countries. They often struggle with low yields due to limited access to key agricultural inputs such as improved seeds, fertilisers and agrochemicals (herbicides and pesticides). They are less likely to rely on irrigation and farm mechanisation. They also have high vulnerability to climate shocks.

Conventional farming practices, including reliance on rain-fed agriculture, the use of low-yielding local seed varieties, sub-optimal input application and heavy dependence on manual labour, are increasingly insufficient to meet the demands of 21st-century food systems.

In recent years, the use of artificial intelligence (AI) tools has been shown to improve input-output efficiency and enable real-time monitoring of crops and livestock. They’ve been shown to conserve soil and water resources, and reduce post-harvest losses particularly in technologically advanced agricultural systems in the US, China and Europe.

We have over 15 years of scholarship in applied economics, development, resource economics and agricultural economics, including technology adoption and sustainable agricultural systems. Our recent study compared AI adoption in agriculture between developed and developing countries.

We examined how artificial intelligence is accessed and used across different regions. Evidence from technologically advanced economies such as Europe, the US, Australia and Japan was analysed alongside studies from Africa, South Asia, Latin America and other low- and middle-income regions.

Our main finding was that AI has strong potential to improve agricultural productivity and resilience. But this potential depends on supportive policies, reliable infrastructure and equitable access. Without these, the technology could reinforce existing inequalities rather than reduce them.

The potential and the gaps

Our review examined:

• patterns of AI adoption: including the extent of uptake across regions, and types of AI applications used in agriculture (such as precision farming, disease detection, yield prediction, and smart irrigation)

• levels of infrastructural readiness: including the availability of electricity, broadband connectivity, digital literacy support, data management systems, smart devices, and extension or technical support services necessary for effective AI adoption

• key concerns around ethics and data governance: including data ownership, privacy and security, informed consent, algorithmic bias, transparency, accountability, and equitable access to AI-driven agricultural technologies.

We also explored how national policies are responding to emerging risks. These include data privacy breaches, cybersecurity vulnerabilities, labour displacement, and unequal access to AI-enabled agricultural technologies. This approach allowed us to capture both global trends and region-specific realities.

AI is increasingly shaping agriculture in developed countries. Technologies such as precision farming tools are helping improve fertiliser use, irrigation, yield prediction and pest management, while also supporting more efficient resource use and greater resilience to climate variability.

The factors that made this possible included:

Digital infrastructure: In many developed countries, reliable internet, satellite systems, cloud platforms and connected sensors enable continuous data collection and analysis. This supports real-time farm decisions and the seamless use of precision agriculture technologies.

Strong institutional support: This has enabled rapid uptake of innovations in agriculture. The support includes established governance frameworks that provide operational clarity on data privacy, transparency and accountability. This enabled more responsible technological innovation.

Reliable electricity: This is essential for AI-driven agriculture. It ensures the continuous operation of digital systems and technologies such as sensors, automated irrigation, drones, and data platforms.

But we found that AI adoption remains limited in developing countries, where smallholder farmers dominate food production. The limiting factors included:

The digital divide: We identified this as the biggest barrier. Farmers often lack stable internet connectivity, affordable devices, or sufficient digital literacy.

Electricity: Shortages hinder the adoption and effective use of AI in agriculture by disrupting the operation of digital tools and infrastructure. These are required for data collection, processing and communication.

Cost: High cost of AI tools and a lack of digital literacy to engage with AI tools effectively.

Limited access to credit: Without sufficient financial capacity, farmers struggle to invest in digital technologies. They cannot afford the upfront purchase costs, installation expenses, or ongoing maintenance and subscription fees required to use AI tools effectively.

AI downsides

We also identified two factors that undermine the adoption of AI in Africa and other developing countries.

First, many AI models are not well suited to developing country contexts. Tools trained on data from industrialised farming systems often perform poorly in local environments. It leads to biased or inaccurate recommendations and increasing risks for vulnerable farmers.

For example, an AI-based yield prediction or pest detection model trained on large-scale monoculture farms in the US or the Netherlands could generate unreliable recommendations when applied to African smallholder farms characterised by mixed cropping, irregular input use, rain-fed agriculture and highly heterogeneous soil conditions.

Second, there are ethical concerns around AI use, particularly the lack of clarity on data ownership and privacy. Weak data governance is most pronounced in developing regions. Farmers often have little control over how their data is collected, used or monetised.

These challenges are not evenly distributed. But the risks are more pronounced in low-income regions, where regulatory systems are weaker and smallholders have fewer resources to manage technological change.

Without appropriate safeguards, AI could reinforce disparities already embedded in global food systems. It also risks deepening existing inequalities, limiting its contribution to sustainable development and food security.

Way forward

AI could transform agriculture in Africa and other developing economies but without the right policies, it may deepen inequality instead.

The priority is to fix the foundations. Reliable electricity, internet access, and affordable digital tools are essential. Without these, AI will remain out of reach for most smallholder farmers. Access to finance, training, and locally relevant data systems will also be critical.

Adoption should be gradual, starting with simple tools like advance mobile advisory services before scaling up.

AI must be inclusive and farmer centred. Done right, it can strengthen food systems. Done poorly, it risks leaving the most vulnerable further behind.

– AI offers promise for agriculture, but smallholder farmers risk being left behind
– https://theconversation.com/ai-offers-promise-for-agriculture-but-smallholder-farmers-risk-being-left-behind-279013

Source: The Conversation – Africa – By Helga Dickow, Associate Researcher at the Arnold Bergstraesser Institut, Freiburg Germany, University of Freiburg

In most multilingual African countries, language policy is a highly charged and controversial issue. It touches on regional identity, religion and political power – as is evident in Chad, in central Africa.

Around 130 languages are spoken in the multi-ethnic and multi-religious Chad. The two official languages are Standard Arabic and French. Neither has its origins in the country and neither is the mother tongue of the majority of the population.

Arabic has shaped the identity of most ethnic groups in northern Chad for several centuries, while French has done so for just under a century, primarily in southern Chad.

Having studied ethnic and religious conflicts in Chad for some time, I can suggest why the country’s new approach to language in education is not just about what happens in schools.

The new education minister, Mahamat-Ahmat Alhabo, issued a circular in April 2026 demanding that, from the coming school year onwards, Standard Arabic be granted the same status as French as language of instruction and examination.

This circular sheds light on the political situation in Chad, both domestically and internationally.

Domestically, the immediate granting of equal status to both languages suggests a deliberate effort to promote the Arabic-speaking economic and political elite. This comes at the expense of the Francophone population, from whom most of the political opposition originates.

It also reflects an ongoing shift away from the former colonial power, France, and an attempt by the current regime under Mahamat Déby to forge closer ties with the Arab world, particularly the United Arab Emirates.

Arabic and French: Islamisation and the colonial legacy

Arabic and French have different historical roots in the country. It is believed that Arabic reached the north of what is now Chad as part of the Islamisation process between the 8th and 11th centuries.

As in other countries, alongside Standard Arabic, a distinct colloquial language known as Chadian Arabic has developed, enhanced by vocabulary from regional local languages.

Today, Standard Arabic is the language in which the Qur’an is taught and recited. It is spoken by a small, predominantly Muslim, educated wealthy elite with close links with Arabic-speaking countries, often through temporary migration for study or work. The majority of those who would call themselves Arabophone generally speak the local Chadian Arabic.

French colonial rule from 1900 to 1960 established French as the language of worship and instruction in the southern regions of the country.

Employment in the colonial administration required knowledge of French. The southern part of Chad embraced the French language more. However, the Islamised north largely rejected it and relied on its own schools instead.

Chadian Arabic and French now serve as two lingua francas nationwide, especially in urban centres. However, they continue to represent different origins and religions: Muslims from the north and Christians from the south.

There are also political power dynamics: part of the Arabophone Muslim elite has held power for more than 40 years.

Bilingualism: requirement and challenge

Like many other states, independent Chad adopted the French education system and French as the official language under the leadership of its Francophone president, Ngarta Tombalbaye.

Although Arabic was recognised as a national language in 1962, French remained the sole official language of administration and education. Consequently, in the first decades following independence, the civil service and political power were dominated by a French-speaking elite.

After years of civil war, in 1978 power was transferred from the predominantly Christian south to the predominantly Islamic north. This was evident in the agreement to recognise Arabic as a second official language. President Félix Malloum, who had only been in power for a few months, agreed with his prime minister, Hissène Habré, who would rule Chad with brutal force from 1982 to 1990, that Arabic should also be included in the constitution.

Following Idriss Déby’s seizure of power in 1990, the 1993 National Conference sought to establish a path towards democratic development in a unified Chad. The conference addressed the issue of language. However, the debate was no longer focused on Arabic or French. Delegates from across the country agreed that the goal should be bilingualism. The question was: Standard Arabic or local Chadian Arabic? Standard Arabic was chosen.

This presented an insurmountable challenge to the already poor education system for the coming decades. There was, and still is, a severe shortage of Arabic teachers and educational materials.

Consequently, few lessons took place, resulting in a low level of Arabic proficiency in state schools. Even universities where courses are taught in Arabic complain that they have to start with basic literacy. Bilingualism in Chad’s schools is still a long way off.

Furthermore, a large proportion of the Francophone population viewed Standard Arabic as a tool of political oppression and refused to learn it.

Language as a political and economic force

According to the circular, Standard Arabic is to be taught from the next academic year onwards with the same number of teaching hours as French. It will also become an exam subject for the final school leaving exam with immediate effect.

This will only benefit the children of the elite. They enhance their language skills by studying at the growing number of private schools that offer high-quality Arabic lessons or by studying abroad.

In practice, the groups that gained their wealth under Idriss Deby’s rule will retain their influence and status.

By contrast, the Francophone former elite will be politically and economically marginalised.

Conclusion

The shift to Standard Arabic reflects the current direction of Chad’s foreign policy. The country has ended its military cooperation with France and is seeking closer ties with the Middle East, particularly with the United Arab Emirates.

Since Idriss Déby’s death, the Emirates have stepped in on several occasions to provide generous financial support. But it’s come with conditions, such as Chad supporting Hemedti in neighbouring Sudan’s civil war, which risks involving Chad in the conflict.

In summary, the language policy of the Chadian regime is not without risk. Excluding a large part of the population from hopes of a better future could lead to conflicts that cannot be resolved peacefully.

– Chad is making Arabic equal to French in schools: the politics behind the move
– https://theconversation.com/chad-is-making-arabic-equal-to-french-in-schools-the-politics-behind-the-move-283313

Source: The Conversation – Africa – By Zayd Waghid, Associate professor, Cape Peninsula University of Technology

South African teacher education qualifications are expected to comply with the Minimum Requirements for Teacher Education Qualifications. But evidence points to gaps in teacher competence and the quality of instruction. Many students who enrol for teaching at South African universities have lower grade 12 results than those studying other degrees. This means universities need to provide support and a good foundation for them to develop as teachers.

Zayd Waghid and Yohana William’s book Preparedness to Teach draws on research between 2015 and 2018 into pre-service teachers’ beliefs, motivations and professional identities, and offers some ideas (which Prof Waghid sets out here) about improving teacher training. Their study involved 324 student teachers – 212 in first year and 112 in fourth year – from two historically disadvantaged universities in South Africa. The research is still relevant today as it captured the formation and development of student teachers’ beliefs, motivations and professional identities over time.

What have you identified as the problems?

First, there is a persistent gap between the theoretical knowledge taught at universities and its practical application in schools. Teacher education curricula generally focus on what to teach, how to teach (including using basic tools), learning through teaching practice, and being aware of the conditions in schools. However, many student teachers still feel unprepared to deal with classroom realities and the wider societal conditions that shape teaching. This disconnect can leave them disempowered in schools.

One of the student teachers we interviewed noted that although modern teaching approaches were taught at university, these were not always accepted in certain government schools.

Secondly, there are challenges of language and multilingualism in diverse classroom contexts. The Language in Education Policy promotes multilingualism and affirms learners’ rights to access education through the official languages in South Africa. But teacher education programmes have been criticised for inadequately preparing student teachers to develop learners’ reading abilities in their home languages. And research shows that African children are most disadvantaged when they do not develop a strong foundation in their mother tongue and are taught in another language.

Thirdly, the power imbalance between universities and schools means that teacher education curricula are designed without consulting current teachers in schools. This has certain implications for the way future teachers are prepared for schools. The book argues that this model works against genuine, mutual co-creation of knowledge.

Fourth, heavy workloads, large classes, learner discipline, weak parental support and limited school resources can weaken motivation and confidence among student teachers. By the fourth year, most student teachers in the study saw teaching as stressful: 76% at one university and 85% at the other agreed or strongly agreed.

Why do these problems matter?

These shortcomings and challenges can be expected to have an impact on the quality of primary education, which is critical for both individual and societal development.

Addressing these issues is vital for transforming an education system shaped by historical inequality, into one that is more equitable, capable of preparing, supporting and retaining high-quality teachers.

The number of graduates studying teaching increased by more than 200% over the ten years between 2011/12 and 2020/21.

How do you fix them?

1. Teacher education should not simply focus on delivering content. It must also help future teachers connect what they learn at university with the real challenges they will face in classrooms.

2. Teacher education programmes must better prepare teachers for multilingual classrooms. This means moving away from the idea that teaching happens in only one language. It means promoting learners’ different languages as a resource for inclusion and learning even if it creates some discomfort. While one cannot be an expert in multiple languages, technology does help here.

3. Universities, schools and communities must work together as an ecosystem in designing teacher education curricula. This will help ensure that teacher training responds to the real social, political and economic conditions of the communities that schools serve. It’s been done before, for example in a study involving a New Zealand university and three schools. In practice, it means that teacher educators and school staff co-teach in schools, and share practices and resources with the idea of making university content more practical and relevant.

4. The book argues that wider changes are needed to restore dignity to the teaching profession. This means improving teachers’ salaries, providing schools with better resources, and reducing heavy workloads. In its 2026 national budget, the South African government allocated R358.556 billion (over US$21 billion) to public schooling, teacher salaries, school operations, nutrition, infrastructure and early childhood development. Education received the largest portion of the budget for spending (23%). However, the question around whether existing resources are used effectively to support teachers in difficult classroom contexts remains vital.

5. Teacher education improves when institutions care about student teachers’ well-being and confidence. Student teachers need to feel safe, supported, and able to cope emotionally throughout their training. In practice, this means establishing a community of practice to build caring relationships. It can happen by recognising their struggles, creating a sense of belonging, and using innovative ways of keeping them connected, while building their confidence.

In a full-time Bachelor of Education programme in South Africa, student teachers must spend a minimum of 20 and maximum of 32 weeks in teaching practice in schools. What we found in the study, was that one student teacher’s positive experience during teaching practice helped her “fall in love” with teaching and strengthened her sense that she was prepared to become a teacher. Teaching practice was a turning point in shaping her identity as a teacher – which is a useful insight.

Mentorship is vital in helping student teachers build confidence and commitment during teaching practice. This is why regular feedback between universities and in-service teachers as mentors during and after teaching practice is critical in further strengthening student teachers’ experiences.

– Student teachers in South Africa face a stressful career: how to prepare them better
– https://theconversation.com/student-teachers-in-south-africa-face-a-stressful-career-how-to-prepare-them-better-281947

Source: The Conversation – Africa – By Amina Ebrahim, Research Fellow at at UNU-WIDER, United Nations University

Bilateral aid to Africa fell by nearly a quarter in 2025, the largest annual decline in the history of official development assistance. Meanwhile, sovereign debt interest payments now consume on average 27% of government revenues across the continent, up from 19% in 2019.

The pressure to fund development from within has never been greater. But meeting it requires African governments to understand their own economies with precision: which tax policies work, which incentives serve their purpose, how fiscal decisions distribute their consequences.

Administrative tax data, the anonymised filings, returns and transaction records generated through the tax system that African revenue authorities already hold, is one of the most powerful tools for answering those questions. South Africa, Uganda and Zambia have built the means to use it, and what they are finding is shaping how they govern.

Each has established a secure research data lab where researchers work with anonymised tax records under strict confidentiality protocols. All three were developed with support from the United Nations University World Institute for Development Economics Research (UNU-WIDER). It provides technical expertise and facilitates knowledge-sharing across countries, while ensuring that the data, the research agenda and the findings are retained by the institutions that use them.

We have been part of that support, from the establishment of the labs and making raw administrative data research-ready, to facilitating partnerships and ensuring findings reach the people placed to act on them.

What these data labs are producing is evidence that has fed into solutions including tax policy reform, budget decisions, labour market programmes and social protection. It can deepen how governments understand the economies they are responsible for, and the people within them.

From research findings to decision

In South Africa, the National Treasury Secure Data Facility, the cornerstone of the Southern Africa Towards Inclusive Economic Development programme, has been doing this work for over a decade. The cumulative impact reflects that longevity. The data has repeatedly illuminated how the economy works, often differently from how policy expected.

Findings have shaped a number of decisions. For example:

• Research revealed that the corporate tax system was quietly favouring debt over equity financing. This was nudging firms to borrow more than they otherwise would, making companies and the economy more fragile in downturns. This informed corporate tax restructuring in Budget 2020.

• Analysis of the Employment Tax Incentive, a wage subsidy for young workers in a country where nearly 60% cannot find work, revealed a more complicated picture of impact than its designers had anticipated. This informed a decision to expand the subsidy during the COVID-19 pandemic.

• Research which describes how much economic activity increases when the government raises spending or cuts taxes emphasised the importance of growth-oriented investments such as infrastructure, education, or public health.

• Analysis of behavioural patterns at tax thresholds provided evidence for designing fairer policies that reduce avoidance and broaden the tax base.

Similarly, in Kampala, Uganda’s commercial capital, adjustments were made to policies based on the use of the data.

• Research conducted through the Uganda Revenue Authority’s secure data lab found that fewer than 15% of firms were paying both national corporate income tax and the local trade licence fee. The gap had existed for years. It had simply never been quantifiable before.

• Separate research revealed that corporate tax incentives were costing approximately US$42 million in forgone revenue. More than half of the benefiting firms likely remained profitable at the full statutory rate of 30%. An incentive regime designed to attract investment was, in measurable terms, more generous than the investment required.

For policymakers, findings like these do not simply describe a problem. They reframe it. The questions have shifted from how to collect more revenue to where the system is working against itself, and what can be changed.

Some examples from Zambia:

• Tax gap research estimated the country’s compliance gap at between 47% and 56%. This helped quantify, for the first time, where revenue was being lost and how audit resources could be better targeted. The findings fed directly into the 2026 budget. The government’s audit strategy was reshaped. And the findings informed the deliberations of the Tax Policy Review Committee.

• Separately, research on VAT administration uncovered a structural inefficiency: large firms generating simultaneous liabilities and credits on the same accounts, a circular flow consuming administrative effort without producing revenue. This was invisible without transaction-level data. When it was identified, the problem was corrected.

From a number to a life

Statistics, even compelling ones, exist in abstraction. What brings them to reality is the chain of consequences, from research finding, to decision, to the life that decision shapes.

Zambia’s domestic revenue contribution to the national budget is rising from 55.7% in 2020 to a planned 73.1% in 2026. This reflects fiscal decisions made with increasing precision and confidence, in a country that now has the tools to interrogate its own tax system rather than rely on external assessments of it.

That stronger revenue base has also made possible a free education initiative that has brought approximately 2.3 million children who were previously out of school back into classrooms. A research lab did not put those children there. Evidence-informed fiscal policy did.

South Africa’s record adds another dimension. Microsimulation modelling showed that the Social Relief of Distress grant was significantly reducing poverty just when a decision about its future needed to be made. The evidence changed what that decision could credibly be. The distinction matters, because it clarifies what these labs are actually for: not the production of research, but the conditions that allow governments to govern better.

The case in practice

Africa’s financing challenge will not be resolved from outside. The most durable path runs through domestic revenue systems that are efficient, fair, and sharpened by what the evidence shows. That requires a particular kind of analytical honesty: the willingness to examine fiscal systems rigorously and act on what the data reveals.

Development economics has long argued that evidence-based policymaking produces better outcomes. South Africa, Uganda and Zambia are making that argument in practice. They are doing this through what they have built, what they have found, and what they have chosen to do because of it.

At a moment when external financing is contracting and debt service is rising, the quality of fiscal decisions is not an academic question. It is the difference between governments that can see their own economies clearly enough to act, and governments that cannot.

The data is already there. The model has been proven. What remains is the will to use it.

– Tax data can be mined to shape better policies. South Africa, Uganda and Zambia show how
– https://theconversation.com/tax-data-can-be-mined-to-shape-better-policies-south-africa-uganda-and-zambia-show-how-281555