AI's deep roots: Preparing Africa's health sector for its evolution

While the public launch of ChatGPT in 2022 brought Artificial Intelligence (AI) into widespread conversation, the technology’s evolution spans nearly eighty years. At a recent Health Security Convention in Mombasa, it became apparent that many health workers have heard of AI but lack a deep understanding of its origins, development, and implications for Africa’s health systems.

Often perceived as a new and complex phenomenon, AI’s potential to enhance healthcare delivery, improve disease surveillance, aid decision-making, and bolster public health responses remains underappreciated. However, appreciating AI’s long history is critical.

The foundational concepts of AI emerged in 1943 with Warren McCulloch and Walter Pitts’s development of the artificial neuron, inspired by the human brain. This laid the groundwork for modern neural networks and deep learning. The term “Artificial Intelligence” itself was coined in 1956 at the Dartmouth Conference, where researchers explored machine simulation of human intelligence.

Since then, AI has progressed through decades of research, marked by significant breakthroughs and setbacks. Key milestones include the development of the Perceptron in 1957, the “AI winter” of 1969, the revival of deep neural networks in the 1980s, and advancements in speech recognition and expert systems in the 1990s. More recent developments include AlexNet’s revolution in image recognition in 2012, AlphaGo’s victory in 2016, the Transformer architecture in 2017, the rise of large language models from 2018-2020, and the public debut of ChatGPT in 2022.

For Africa, which grapples with challenges like disease outbreaks, workforce shortages, and weak surveillance, AI offers a powerful opportunity to augment, not replace, health workers. AI can accelerate outbreak analysis, enhance disease surveillance, support training, improve health communication, and aid emergency decision-making.

Organizations in Africa already generate substantial public health data that could fuel smarter surveillance and response systems. However, there’s a risk of the continent being left behind if its health workforce doesn’t engage with and shape AI’s application. The primary danger lies not in the technology itself, but in exclusion.

As most AI systems are developed outside Africa, using datasets that may not reflect local realities, it is imperative for the continent to invest in digital literacy, ethical AI governance, local datasets, and workforce preparedness. The focus for AI in Africa should shift from fear and myth to preparedness, innovation, and empowering health professionals to utilize AI for stronger health systems and better public health outcomes.

Source: Daily Monitor (Uganda)