5 Ways AI is Boosting Citizen Engagement in Africa’s Democracies


Article by Peter Agbesi Adivor: “Artificial Intelligence (AI) is increasingly influencing democratic participation across Africa. From campaigning to voter education, AI is transforming electoral processes across the continent. While concerns about misinformation and government overreach persist, AI also offers promising avenues to enhance citizen engagement. This article explores five key ways AI is fostering more inclusive and participatory democracies in Africa.

1. AI-Powered Voter Education and Campaign

AI-driven platforms are revolutionizing voter education by providing accessible, real-time information. These platforms ensure citizens receive standardized electoral information delivered to them on their digital devices regardless of their geographical location, significantly reducing the cost for political actors as well as state and non-state actors who focus on voter education. They also ensure that those who can navigate these tools easily access the needed information, allowing authorities to focus limited resources on citizens on the other side of the digital divide.

 In Nigeria, ChatVE developed CitiBot, an AI-powered chatbot deployed during the 2024 Edo State elections to educate citizens on their civic rights and responsibilities via WhatsApp and Telegram. The bot offered information on voting procedures, eligibility, and the importance of participation.

Similarly, in South Africa, the Rivonia Circle introduced Thoko the Bot, an AI chatbot designed to answer voters’ questions about the electoral process, including where and how to vote, and the significance of participating in elections.

These AI tools enhance voter understanding and engagement by providing personalized, easily accessible information, thereby encouraging greater participation in democratic processes…(More)”.

Europe’s dream to wean off US tech gets reality check


Article by Pieter Haeck and Mathieu Pollet: “..As the U.S. continues to up the ante in questioning transatlantic ties, calls are growing in Europe to reduce the continent’s reliance on U.S. technology in critical areas such as cloud services, artificial intelligence and microchips, and to opt for European alternatives instead.

But the European Commission is preparing on Thursday to acknowledge publicly what many have said in private: Europe is nowhere near being able to wean itself off U.S. Big Tech.

In a new International Digital Strategy the EU will instead promote collaboration with the U.S., according to a draft seen by POLITICO, as well as with other tech players including China, Japan, India and South Korea. “Decoupling is unrealistic and cooperation will remain significant across the technological value chain,” the draft reads. 

It’s a reality check after a year that has seen calls for a technologically sovereign Europe gain significant traction. In December the Commission appointed Finland’s Henna Virkkunen as the first-ever commissioner in charge of tech sovereignty. After few months in office, European Parliament lawmakers embarked on an effort to draft a blueprint for tech sovereignty. 

Even more consequential has been the rapid rise of the so-called Eurostack movement, which advocates building out a European tech infrastructure and has brought together effective voices including competition economist Cristina Caffarra and Kai Zenner, an assistant to key European lawmaker Axel Voss.

There’s wide agreement on the problem: U.S. cloud giants capture over two-thirds of the European market, the U.S. outpaces the EU in nurturing companies for artificial intelligence, and Europe’s stake in the global microchips market has crumbled to around 10 percent. Thursday’s strategy will acknowledge the U.S.’s “superior ability to innovate” and “Europe’s failure to capitalise on the digital revolution.”

What’s missing are viable solutions to the complex problem of unwinding deep-rooted dependencies….(More)”

Leveraging Citizen Data to Improve Public Services and Measure Progress Toward Sustainable Development Goal 16


Paper by Dilek Fraisl: “This paper presents the results of a pilot study conducted in Ghana that utilized citizen data approaches for monitoring a governance indicator within the SDG framework, focusing on indicator 16.6.2 citizen satisfaction with public services. This indicator is a crucial measure of governance quality, as emphasized by the UN Sustainable Development Goals (SDGs) through target 16.6 Develop effective, accountable, and transparent institutions at all levels. Indicator 16.6.2 specifically measures satisfaction with key public services, including health, education, and other government services, such as government-issued identification documents through a survey. However, with only 5 years remaining to achieve the SDGs, the lack of data continues to pose a significant challenge in monitoring progress toward this target, particularly regarding the experiences of marginalized populations. Our findings suggest that well-designed citizen data initiatives can effectively capture the experiences of marginalized individuals and communities. Additionally, they can serve as valuable supplements to official statistics, providing crucial data on population groups typically underrepresented in traditional surveys…(More)”.

The Next Wave of Innovation Districts


Article by Bruce Katz and Julie Wagner: “A next wave of innovation districts is gaining momentum given the structural changes underway in the global economy. The examples cited above telegraph where existing innovation districts are headed and explain why new districts are forming. The districts highlighted and many others are responding to fast-changing and highly volatile macro forces and the need to de-riskdecarbonize, and diversify talent.

The next wave of innovation districts is distinctive for multiple reasons.

  • The sectors leveraging this innovation geography expand way beyond the traditional focus on life sciences to include advanced manufacturing for military and civilian purposes.
  • The deeper emphasis on decarbonization is driving the use of basic and applied R&D to invent new clean technology products and solutions as well as organizing energy generation and distribution within the districts themselves to meet crucial carbon targets.
  • The stronger emphasis on the diversification of talent includes the upskilling of workers for new production activities and a broader set of systems to drive inclusive innovation to address long-standing inequities.
  • The districts are attracting a broader group of stakeholders, including manufacturing companies, utilities, university industrial design and engineering departments and hard tech startups.
  • The districts ultimately are looking to engage a wider base of investors given the disparate resources and traditions of capitalization that support defense tech, clean tech, med tech and other favored forms of innovation.

Some regions or states are also seeking ways to connect a constellation of districts and other economic hubs to harness the imperative to innovate accentuated by these and other macro forces. The state of South Australia is one such example. It has prioritized several innovation hubs across this region to foster South Australia’s knowledge and innovation ecosystem, as well as identify emerging economic clusters in industry sectors of global competitiveness to advance the broader economy…(More)”.

Leading, not lagging: Africa’s gen AI opportunity


Article by Mayowa Kuyoro, Umar Bagus: “The rapid rise of gen AI has captured the world’s imagination and accelerated the integration of AI into the global economy and the lives of people across the world. Gen AI heralds a step change in productivity. As institutions apply AI in novel ways, beyond the advanced analytics and machine learning (ML) applications of the past ten years, the global economy could increase significantly, improving the lives and livelihoods of millions.1

Nowhere is this truer than in Africa, a continent that has already demonstrated its ability to use technology to leapfrog traditional development pathways; for example, mobile technology overcoming the fixed-line internet gap, mobile payments in Kenya, and numerous African institutions making the leap to cloud faster than their peers in developed markets.2 Africa has been quick on the uptake with gen AI, too, with many unique and ingenious applications and deployments well underway…(More)”.

Across McKinsey’s client service work in Africa, many institutions have tested and deployed AI solutions. Our research has found that more than 40 percent of institutions have either started to experiment with gen AI or have already implemented significant solutions (see sidebar “About the research inputs”). However, the continent has so far only scratched the surface of what is possible, with both AI and gen AI. If institutions can address barriers and focus on building for scale, our analysis suggests African economies could unlock up to $100 billion in annual economic value across multiple sectors from gen AI alone. That is in addition to the still-untapped potential from traditional AI and ML in many sectors today—the combined traditional AI and gen AI total is more than double what gen AI can unlock on its own, with traditional AI making up at least 60 percent of the value…(More)”

Activating citizens: the contribution of the Capability Approach to critical citizenship studies and to understanding the enablers of engaged citizenship


Paper by Anna Colom and Agnes Czajka: “The paper argues that the Capability Approach can make a significant contribution to understanding the enablers of engaged citizenship. Using insights from critical citizenship studies and original empirical research on young people’s civic and political involvement in western Kenya, we argue that it is useful to think of the process of engaged citizenship as comprised of two distinct yet interrelated parts: activation and performance. We suggest that the Capability Approach (CA) can help us understand what resources and processes are needed for people to not only become activated but to also effectively perform their citizenship. Although the CA is rarely brought into conversation with critical citizenship studies literatures, we argue that it can be useful in both operationalising the insights of critical citizenship studies on citizenship engagement and illustrating how activation and performance can be effectively supported or catalysed….(More)”

How Behaviorally-Informed Technologies Are Shaping Global Aid


Article by Heather Graci: “Contraceptives are available in Sub-Saharan Africa, but maternal deaths caused by unwanted pregnancies are still rampant. Refugee agencies support those forced to flee their homes, but don’t always know where they’ll go—or what they’ll need when they get there. AI-powered tutors provide crucial support to kids struggling in under-resourced schools, but may not treat their students equally. 

These are the sorts of humanitarian challenges that featured at the seventh annual United Nations Behavioural Science Week earlier this month. Each year, the UN Behavioural Science Group brings together researchers and practitioners from inside and outside of the UN to discuss how to use behavioral science for social good. Practitioners are exposed to the latest research that could inform their work; academics glimpse how their ideas play out amid the chaos of the real world. And everyone learns about projects happening beyond their focus area. Experts in healthcare, finance, education, peace and security, and beyond share a common language—and common solutions—in behavioral science. 

This year technology was a central theme. Panelists from organizations like UNICEF and the World Bank joined academic experts from behavioral science, data science, and AI to discuss how thoughtful, behaviorally-informed technologies can bolster global development and aid efforts. 

I’ve curated three sessions from the week that capture the different ways this is happening. Digital assistants that boost the capacity of health care workers or teachers. Predictive models that help aid agencies send the right resources to the right regions. And just as AI can exacerbate bias, it can mitigate it too—as long as we understand how it intersects with different cultures as it’s deployed around the world…(More)”.

Technical Tiers: A New Classification Framework for Global AI Workforce Analysis


Report by Siddhi Pal, Catherine Schneider and Ruggero Marino Lazzaroni: “… introduces a novel three-tiered classification system for global AI talent that addresses significant methodological limitations in existing workforce analyses, by distinguishing between different skill categories within the existing AI talent pool. By distinguishing between non-technical roles (Category 0), technical software development (Category 1), and advanced deep learning specialization (Category 2), our framework enables precise examination of AI workforce dynamics at a pivotal moment in global AI policy.

Through our analysis of a sample of 1.6 million individuals in the AI talent pool across 31 countries, we’ve uncovered clear patterns in technical talent distribution that significantly impact Europe’s AI ambitions. Asian nations hold an advantage in specialized AI expertise, with South Korea (27%), Israel (23%), and Japan (20%) maintaining the highest proportions of Category 2 talent. Within Europe, Poland and Germany stand out as leaders in specialized AI talent. This may be connected to their initiatives to attract tech companies and investments in elite research institutions, though further research is needed to confirm these relationships.

Our data also reveals a shifting landscape of global talent flows. Research shows that countries employing points-based immigration systems attract 1.5 times more high-skilled migrants than those using demand-led approaches. This finding takes on new significance in light of recent geopolitical developments affecting scientific research globally. As restrictive policies and funding cuts create uncertainty for researchers in the United States, one of the big destinations for European AI talent, the way nations position their regulatory environments, scientific freedoms, and research infrastructure will increasingly determine their ability to attract and retain specialized AI talent.

The gender analysis in our study illuminates another dimension of competitive advantage. Contrary to the overall AI talent pool, EU countries lead in female representation in highly technical roles (Category 2), occupying seven of the top ten global rankings. Finland, Czechia, and Italy have the highest proportion of female representation in Category 2 roles globally (39%, 31%, and 28%, respectively). This gender diversity represents not merely a social achievement but a potential strategic asset in AI innovation, particularly as global coalitions increasingly emphasize the importance of diverse perspectives in AI development…(More)”

Mind the (Language) Gap: Mapping the Challenges of LLM Development in Low-Resource Language Contexts


White Paper by the Stanford Institute for Human-Centered AI (HAI), the Asia Foundation and the University of Pretoria: “…maps the LLM development landscape for low-resource languages, highlighting challenges, trade-offs, and strategies to increase investment; prioritize cross-disciplinary, community-driven development; and ensure fair data ownership…

  • Large language model (LLM) development suffers from a digital divide: Most major LLMs underperform for non-English—and especially low-resource—languages; are not attuned to relevant cultural contexts; and are not accessible in parts of the Global South.
  • Low-resource languages (such as Swahili or Burmese) face two crucial limitations: a scarcity of labeled and unlabeled language data and poor quality data that is not sufficiently representative of the languages and their sociocultural contexts.
  • To bridge these gaps, researchers and developers are exploring different technical approaches to developing LLMs that better perform for and represent low-resource languages but come with different trade-offs:
    • Massively multilingual models, developed primarily by large U.S.-based firms, aim to improve performance for more languages by including a wider range of (100-plus) languages in their training datasets.
    • Regional multilingual models, developed by academics, governments, and nonprofits in the Global South, use smaller training datasets made up of 10-20 low-resource languages to better cater to and represent a smaller group of languages and cultures.
    • Monolingual or monocultural models, developed by a variety of public and private actors, are trained on or fine-tuned for a single low-resource language and thus tailored to perform well for that language…(More)”

Designing New Institutions and Renewing Existing Ones – A Playbook


UNDP Report: “The world has long depended on public institutions to solve problems and meet needs — from running schools to building roads, taking care of public health to defense. Today, global challenges like climate change, election security, forced migration, and AI-induced unemployment demand new institutional responses, especially in the Global South.

The bad news? Many institutions now struggle with public distrust, being seen as too wasteful
and inefficient, unresponsive and ineffective, and sometimes corrupt and outdated.
The good news? Fresh methods and models inspired by innovations in government, business, and civil
society are now available that can help us rethink institutions — making them more public results
oriented, agile, transparent, and fit for purpose. And ready for the future…(More)”.