Challenges to AI Development in Africa

Introduction

This blog post examines the five primary obstacles confronting Artificial Intelligence (AI) development and deployment in Africa. When training AI models, it is important to use data that is specific to the context in which the model will be used. AI models need context to understand data, just like humans do.

This explains why AI models that are trained on data from outside of Africa can produce biased or inaccurate information about Africa. AI is transforming societies that invest in technological infrastructure because they easily collect and structure data, which they then use to develop AI solutions. In this age of digital transformation, African countries are lagging in technological advancements.

I acknowledge that not all African countries are at the same stage of technological advancement and the development of artificial intelligence would definitely differe per country. However, the consensus is that African countries need to catch up with other countries that have developed AI and advanced in technology. I explore five significant challenges that impede African countries from developing in AI.

Lack of data
AI models are trained to operate on large data sets. AI training is the process of teaching AI systems to make decisions based on data, using large datasets and powerful computing platforms. In addition to training AI models, these models require access to significant and high-quality data to operate properly.

Unfortunately, AI is struggling to pick up in Africa because most African countries do not generate enough data, and their data sets are improperly stored and structured. Africa’s lack of datasets and information makes it challenging to train AI models, which rely on algorithms that learn from data.

This is a significant obstacle to the development of AI in Africa. Since AI models depend on algorithms that shape and inform AI to perceive and interpret data, its absence is detrimental to the development of AI in Africa.

Lack of Technical Skills
The development and implementation of AI require a workforce skilled in machine learning, data science, and related fields. In a previous blogpost, I argued that although Africa’s youth represent the continent’s hope and future, the current educational model does not provide them with the required skills and tools to compete with the rest of the world.

Lack of Funding
AI, like other forms of research discipline, requires significant financial investments for infrastructure, human resources, and other related investments. Most African governments struggle to meet basic needs for their countries and consider investments in AI a supplementary and unwanted investment.

While big tech companies including Google, Facebook, Microsoft, and Amazon opened technology and startup hubs for ICT investments in vital African markets, inluding South Africa, Nigeria, Egypt, and Kenya in 2022, African tech startups are starting to lose investors and investments.

According to startup funding tracker Africa, African startups raised $300 million in funding from venture capitalists (VCs) in the third quarter of 2023, marking the third consecutive quarter of decline in funding. However, African governments need to allow African AI startups to collaborate with governments, businesses, and international organizations, which is essential to overcome the funding obstacle. Strategic partnerships and funding mechanisms can unlock the financial resources needed to advance AI projects.

Lack of necessary infrastructure
A robust technological infrastructure is essential for successfully deploying artificial intelligence (AI) solutions. AI requires hardware infrastructure that can store and scan massive amounts of data, in the petabyte or exabyte range.

This includes reliable internet access, computing resources, data centres, and advanced hardware. However, many parts of Africa need help with these challenges, as they have limited access to high-speed internet and inadequate computing resources.

Investing in digital infrastructure is crucial to bridge this gap and enable Africa to fully realise AI’s potential. Electrification is also necessary for the development and deployment of AI in Africa.

Ethical concerns
Ethical considerations are vital to deploying AI responsibly. All crucial stakeholders must carefully examine issues like bias, privacy, surveillance, content moderation and job displacement that will arise due to Ai development and deployment in Africa. Since AI is a model where systems are trained to perceive and interpret data, some stakeholders can purposely design AI to perform negative societal roles.

For example, some government and industry actors may decide to deploy AI to moderate social media content in a particular way that could target a class of people from expressing themselves online. To resolve this issue, stakeholders must adopt robust ethical frameworks and regulations to facilitate a level playing ground for all.

Conclusion
AI can catalyze Africa’s transformation towards development and modernity, but the identified challenges must be addressed primarily through investment and research in science, technology, engineering, and math (STEM). These disciplines are essential for the development, collection, processing, and structuring of data, which is advancing the training of AI models.

Specifically, African governments need to partner with technology companies and ensure that they set up operations in Africa. This will help to collect, sort, treat, and deploy continent-specific data, which is essential for the development of AI solutions that are tailored to Africa’s needs.

The ethical concerns surrounding the deployment of AI and data require the active participation of all stakeholders, including civil society organizations, research institutions, governments, and industry. Together, they can develop effective legal frameworks for the deployment of AI.