AI and the New Africa (Part I): Data is the New Oil, AI is the New Combustion Engine: Could Africa be the New Silicon Valley?
Let’s keep the title aside for a minute. Now, many people, especially in Africa, likely do not realize the dramatic changes sweeping the world in recent times. Accelerated progress in scientific discoveries and technological breakthroughs in the past few decades have led to immense developments which in turn ushered in transformative changes in many aspects of our daily lives. This has further accelerated the progress of other technological developments. Every industry is expected to disrupt toward efficiency, age-old systems are totally transformed and entirely new economic and social orders are being created at rates almost inconceivable even in recent times.
Among the key developments leading this transformation is Artificial Intelligence (AI). AI is basically intelligence exhibited by smart machines. Recently AI is almost everywhere there is technology. To put this in perspective, AI is what enables a digital device to see and recognize objects (e.g., read a barcode), understand and reply to normal speech (Siri; Apple, OK; Google”), make decisions and learn to change its logical processes and behavior as it analyzes large amounts of data for AI application such as in research (Pharma.ai from Insilico Medicine) and data bits in the distributed memory known as cloud (IBM’s Watson). It also helps machines move and handle things (your robots) and so much more.
AI has been a buzz among tech geeks since the early beginnings of computerization. The term was actually mentioned as early as the 1950s. Nowadays it has recently become the hottest talk of the town by entering into mainstream discussions. Its usage rose to popularity due to the increasing computer processing power, advances in programming techniques and generation of massive amounts of data also known as “Big Data” (more on this later in the series). Some main goals of AI are natural language processing, learning and self-evolving, reasoning, and planning. Many people mistakenly refer to AI exclusively as robots or similar devices that move and handle objects. But this is not the case since AI is so much more than that. In fact, robotics only makes use of some aspects of AI. Overall, AI involves sophisticated software applications developed by humans to do tasks far quicker than humanly possible and with higher accuracy.
Recently two key areas of AI; Machine Learning (ML) and Deep Learning (DL), have received significant attention and contributed in no small measure to the fascinating advances in AI. ML, which used to be something only computer scientists in server rooms discussed, has become a trendy topic, alongside big data and deep learning. To put it simply, ML is about machines developing algorithms that allow them to learn and be capable of making predictions. Basically, it is the ability of machines to go beyond what they are programmed to do and actually teach themselves in the process. For example, websites or apps like YouTube or Netflix predicting videos or movies you might want to watch, and devices that could update their models as new data is received without human intervention. Think of companies learning to track new leads, suggesting products for up-sales, and monitoring sales cycle times. Basically, algorithms process datasets, usually very large amounts, with the ability to detect and extrapolate patterns and adapt to varied circumstances in response to the insights from the processed data.
DL is basically a technique for implementing ML and has enabled many practical applications of ML and by extension the overall field of AI. DL is sort of like mimicking the human brain in solving problems and involves techniques like neural networks. We are not going to go into details at this point. But essentially, DL breaks down tasks in ways that make all kinds of machine enhancing processes seem possible. It helped with so much of the improvements we have in recent times such as driverless cars, better preventive healthcare, and so on. DL has notably been a big contribution to the field of AI as a whole.
For starters, we are entering an era when data is the new oil and AI is the new combustion engine, and African countries should pull the resources to develop and dominate the new generation of AI-driven industry, especially for important areas like healthcare. We have discussed this in an earlier post and more on this later. But we might be wondering; why the analogy between oil and data and between AI and combustion engine? To appreciate this effort, we find that on a closer observation, it is clear that AI which relies mainly on data just as combustion engine relies on oil, is transforming society at a degree and velocity that may, in fact, be greater than the impact of the combustion engine.
More surprising could be the parallel between Africa and Silicon Valley (SV); Africa is a continent and SV is just about a collection of municipalities and towns. Perhaps, why do we think Africa could, in fact, be the new SV or why new SV at all? Why not something else? Even Fox News shared a similar sentiment recently. To be clear, we are not here to merely compare for the sake of comparing; that would likely not make much sense. What we are aiming at here is to look at facts that are worth delving into and to draw some sort of healthy benchmarking for the purpose of learning and gaining of insights. For our purpose, it is simply a matter of scale. It is obvious SV has contributed a lot to our civilization and the current state of humanity and many of these achievements are just damn laudable. Now just imagine for a minute what the global impact would be like if we could scale the developments in SV in Africa. This would be even more meaningful from a humanitarian point of view (considering the needs of Africa) and massively more transformative for humanity as a whole.
Does this sound utopian? Well, maybe. And is it somehow practicable? Well, possibly.
In any case, this series would not really be about providing answers and proffering solutions. What we would mostly do is try to explore options and raise questions for further debate and deliberations that could benefit not just Africa but almost everywhere in the world.
See you next week on part deux.
About the Author
Iraneus Ogu directs the Africa Artificial Intelligence and Blockchain for Healthcare Initiative at Insilico Medicine, Inc. In addition to tech developments, he works on Longevity and Aging Interventions with his research efforts focusing on neuroregeneration. He also has a background in Pharmaceutical Sciences at the University of Greenwich where his research focused on controlled-release dosage forms.
