The impact that artificial intelligence (AI) and machine learning (ML) can have on healthcare can’t be understated. While most analysts consider the potential impact on Western medicine and the US healthcare system, the greatest near-term value for patients is in developing countries. AI in healthcare will become the next leapfrog technology for developing nations. To understand AI’s potential to be a leapfrog technology within healthcare in developing countries, we can learn lessons from the telecommunications, banking and energy sectors.
Africa lagged behind the Western world for many years in connectivity due to a lack of investment in physical telephone line infrastructure. After a significant investment in 4G infrastructure and the reduced cost of smartphones, rural parts of Africa have become connected to the rest of the world.
Similarly, China has experienced great growth in connectivity. China launched 4G in 2013, building the world’s largest 4G network within just 4 years.[i] And since July 2019, they’ve had over 1.24 billion 4G users.[ii] The company Xiao Mi played a vital role in the last decade in China, placing cheap, high quality smartphones in the hands of Chinese. The rise of smartphone ownership and 4G has benefited both urban and rural areas. “Farmers can sell their produce online through e-commerce sites”, “buy crucial equipment safer and quicker” and “receive agricultural information.”[iii] Furthermore, poverty is being alleviated through online education.[iv]
In the 1990s and early 2000s, there was a lack of banks in rural Africa to support money transfers. Coupled with the growth of the wireless telecom industry, services like M-Pesa allowed customers to send and receive money from their mobile phones, which enabled commerce, increased financial transaction security and provided microloans to start businesses.
For awhile, China also seemed to lag behind in banking by not adopting one of the primary payment methods of the West—credit cards. But now, much of China uses payment apps instead of cash. Citizens in rural areas without access to physical banks now have access to digital banks through their phones. WeChat and Alipay have become the primary money transaction systems. And they are leading toward a cashless society. In 2018, around 83% of all payments in China were made via mobile payment.[v] The two systems allow access to “financial services, such as investment and insurance products, e-commerce services, and convenient solutions for bill pay.”[vi]
Energy is one of our most essential resources. But it requires a large capital investment in infrastructure and distribution networks. Rural African communities lack electric grids, and many predicted that countries would invest in infrastructure over time. Thanks to renewable solar energy, solar panels can be installed on private homes eliminating the need for investing in an electric grid. The company Black Star Energy sells panels to customers who pay monthly payments that can be made via mobile phone.
The case for healthcare
Access to doctors and medication is a major problem in rural parts of developing countries. But AI can be a leapfrog technology that reduces the need to build out infrastructure in remote areas. There is a huge opportunity for ML and AI to improve medical diagnostics in this part of the world, help doctors treat a larger number of patients and quickly prioritize those in greatest need.
A great example is how Google is using ML to prevent blindness in diabetic patients in rural India. Over 70 million people suffer from diabetes in India, making it impossible to screen them all for diabetic retinopathy at an early stage. A ML algorithm was trained to diagnose the stage of retinopathy, enabling doctors to screen more patients and help those in greatest need. This is the power of AI—helping millions of patients get screened and diagnosed while enabling doctors to work more efficiently.
In the future, the smartphone will be the virtual doctor in developing countries. Smartphones will be used not only through telemedicine, but also through AI-driven diagnostics and automatically prescribed medications.
Imagine a world where the patient inputs their symptoms into an application, uploads pictures of their injury or sickness from their phone, is automatically diagnosed and can receive medication the following day by mail or drone. After the medicine is received, an AI chatbot can follow-up to ensure that medications are taken properly and check with the patients to see if the symptoms persist.
There is likely to be a reluctance to these types of systems in the Western world due to the preference of human interaction and distrust in tech-only diagnostics. But if you live in a remote area in a developing country and do not have access to a doctor, these types of AI services could be life-saving.
The secondary benefits of deploying an AI doctor system come from the data. By collecting patient, sickness and geolocation data, governments can understand where to better place healthcare infrastructure investments to serve the most urgent patient needs. Improved data collection can help governments understand which environmental factors are causing illnesses, such as cancer, and lead to remediation efforts that help reduce casualties over time.
The applications for AI in healthcare are endless. But the greatest patient value will be felt in the developing world where the power of AI has the opportunity to dramatically improve healthcare delivery for millions of people.