Chinasa T. Okolo

The Brookings Institution · Center for Technology Innovation

In light of prominent discourse around the negative implications of generative AI, an emerging area of research is investigating the current and estimated impacts of AI-generated propaganda on African citizens participating in elections. Throughout Africa, there have already been suspected cases of AI-generated propaganda influencing electoral outc...

The increasing usage of AI in high-stakes decision-making underscores a pressing need for various stakeholders to understand AI, learn how to identify AI-generated content, and become aware of its societal risks. We detail outcomes from engaging underrepresented secondary school students in a 5-day workshop series consisting of brief lectures, hand...

AI for Social Good (AI4SG) has been advocated as a way to address social impact problems using emerging technologies, but little research has examined practitioner motivations behind building these tools and how practitioners make such tools understandable to stakeholders and end users, e.g., through leveraging techniques such as explainable AI (XA...

AI-driven tools are increasingly deployed to support low-skilled community health workers (CHWs) in hard-to-reach communities in the Global South. This paper examines how CHWs in rural India engage with and perceive AI explanations and how we might design explainable AI (XAI) interfaces that are more understandable to them. We conducted semi-struct...

Those best positioned to profit from the proliferation of artificial intelligence (AI) systems are those with the most economic power. Extant global inequality has motivated Western tech companies to involve more diverse groups in the development and application of AI systems, including hiring local talent and establishing extra-national data cente...

This white paper is the output of a multidisciplinary workshop in Nairobi (Nov 2023). Led by a cross-organisational team including Microsoft Research, NEPAD, Lelapa AI, and University of Oxford. The workshop brought together diverse thought-leaders from various sectors and backgrounds to discuss the implications of Generative AI for the future of w...

The increasing development of machine learning (ML) models and adoption of artificial intelligence (AI) tools, particularly generative AI, has dramatically shifted practices around data, spurring the development of new industries centered around data labeling and revealing new forms of exploitation, including illegal data scraping for AI training d...

This is the interim publication of the first International Scientific Report on the Safety of Advanced AI. The report synthesises the scientific understanding of general-purpose AI -- AI that can perform a wide variety of tasks -- with a focus on understanding and managing its risks. A diverse group of 75 AI experts contributed to this report, incl...

Artificial Intelligence for Social Good (AI4SG) has emerged as a growing body of research and practice exploring the potential of AI technologies to tackle social issues. This area emphasizes interdisciplinary partnerships with community organizations, such as non-profits and government agencies. However, amidst excitement about new advances in AI...

AI for Social Good (AI4SG) has been advocated as a way to address social impact problems using emerging technologies, but little research has examined practitioner motivations behind building these tools and how practitioners make such tools understandable to stakeholders and end users, e.g., through leveraging techniques such as explainable AI (XA...

Artificial Intelligence for Social Good (AI4SG) has emerged as a growing body of research and practice exploring the potential of AI technologies to tackle social issues. This area emphasizes interdisciplinary partnerships with community organizations, such as non-profits and government agencies. However, amidst excitement about new advances in AI...

In light of prominent discourse around the negative implications of generative AI, an emerging area of research is investigating the current and estimated impacts of AI-generated propaganda on African citizens participating in elections. Throughout Africa, there have already been suspected cases of AI-generated propaganda influencing electoral outc...

Artificial Intelligence (AI) requires new ways of evaluating national technology use and strategy for African nations. We conduct a survey of existing 'readiness' assessments both for general digital adoption and for AI policy in particular. We conclude that existing global readiness assessments do not fully capture African states' progress in AI r...

This white paper is the output of a multidisciplinary workshop in Nairobi (November 2023), led by a cross-organisational team including Microsoft Research, Microsoft Philanthropies, University of Pretoria, NEPAD, Lelapa AI, and Oxford University. The workshop brought together diverse thought-leaders from various sectors and backgrounds to discuss t...

The International Scientific Report on the Safety of Advanced AI interim report sets out an up-to-date, science-based understanding of the safety of advanced AI systems. The independent, international, and inclusive report is a landmark moment of international collaboration. It marks the first time the international community has come together to s...

As generative AI applications such as ChatGPT, Midjourney, DALL·E, Bard, and others increase in ubiquity, concerns about the negative implications of these technologies are becoming more present in public discourse. However, little research has examined the impact that generative AI stands to have on African consumers and users who may be affected...

AI for Social Good (AI4SG) has been advocated as a way to address social impact problems using emerging technologies, but little research has examined practitioner motivations behind building these tools and how practitioners make such tools understandable to stakeholders and end users, e.g. through leveraging techniques such as explainable AI (XAI...

As artificial intelligence (AI) development accelerates globally and concerns regarding its use grow, the need for AI governance has reached an unprecedented level of urgency. With only seven African nations (Benin, Egypt, Ghana, Mauritius, Rwanda, Senegal, and Tunisia) having drafted national AI strategies and none implementing formal AI regulatio...

As generative AI applications such as ChatGPT, Midjourney, DALL·E, Bard, and others increase in ubiquity, concerns about the negative implications of these technologies are becoming more present in public discourse. However, little research has examined the impact that generative AI stands to have on African consumers and users who may be affected...

As researchers and technology companies rush to develop artificial intelligence (AI) applications that aid the health of marginalized communities, it is critical to consider the needs of community health workers (CHWs), who will be increasingly expected to operate tools that incorporate these technologies. My work in this dissertation shows that th...

In healthcare, the role of AI is continually evolving, and understanding the challenges its introduction poses on relationships between healthcare providers and patients will require a regulatory and behavioral approach that can provide a guiding base for all users involved. In this paper, we present IAC (Informing, Assessment, and Consent), a fram...

Explainable AI (XAI) is often promoted with the idea of helping users understand how machine learning models function and produce predictions. Still, most of these benefits are reserved for those with specialized domain knowledge, such as machine learning developers. Recent research has argued that making AI explainable can be a viable way of makin...

This open access book contributes to the discourse of Responsible Artificial Intelligence (AI) from an African perspective. It is a unique collection that brings together prominent AI scholars to discuss AI ethics from theoretical and practical African perspectives and makes a case for African values, interests, expectations and principles to under...

This chapter provides an analysis into the factors that impact the effective adoption and successful implementation of artificial intelligence (AI) technologies in Africa. The study begins by defining the concept of “responsible AI” and what this means specifically for technologies developed and used within Africa. Further sections within the chapt...

Over the past 60 years, artificial intelligence (AI) has made significant progress, but most of its benefits have failed to make a significant impact within the Global South. Current practices that have led to biased systems will prevent AI from being actualized unless significant efforts are made to change them. As technical advances in AI and an...

In healthcare, the role of AI is continually evolving and understanding the challenges its introduction poses on relationships between healthcare providers and patients will require a regulatory and behavioural approach that can provide a guiding base for all users involved. In this paper, we present ACIPS (Acceptability, Comfortability, Informed C...

Since the start of the pandemic, the proliferation of fake news and misinformation has been a constant battle for health officials and policy makers as they work to curb the spread of COVID-19. In areas within the Global South, it can be difficult for officials to keep track of the growth of such false information and even harder to address the rea...

Those best-positioned to profit from the proliferation of artificial intelligence (AI) systems are those with the most economic power. Extant global inequality has motivated Western institutions to involve more diverse groups in the development and application of AI systems, including hiring foreign labour and establishing extra-national data cente...

As AI becomes integrated throughout the world, its potential for impact within low-resource regions around the Global South have grown. AI research labs from tech giants like Microsoft, Google, and IBM have a significant presence in countries such as India, Ghana, and South Africa. The work done by these labs is often motivated by the potential imp...

Mobile health (mHealth) is formally defined as “the provision of health services and information via mobile technologies” and has been used to help diagnose infectious diseases, record patient information, and manage medication adherence. The use of mHealth is burgeoning in Sub-Saharan Africa and throughout the rest of the global south due to the p...

Men and women spend hundreds of millions of dollars on hair care products yearly in the U.S. Hair typing is deemed important to women and men because it helps women identify products that may be beneficial to their overall hair health. This work describes different hair typing systems and proposes a recognition system that can be used to classify h...

WebGazer uses computer webcams to track the eye-gaze locations of users in real-time. This eye-tracking library is solely implemented in JavaScript and can be easily integrated within a web browser. WebGazer uses a model implemented by another JavaScript library, clmtrackr to fit facial models on faces tracked through video. This library allows Web...