Using Artificial Intelligence to address society’s real-life problems
The applications of AI in healthcare are boundless, and healthcare, in turn, is one of the numerous areas where AI can have a significant impact
Given its wide and growing range of capabilities and applications, Artificial Intelligence (AI) can be effectively used to improve the state of public healthcare in many parts of the world. And while AI is being increasingly used in clinics to treat individual patients, its application in public health systems has been far less in comparison. From my experience of studying the social impact of computing in developing worlds and multiple areas of public health, I strongly believe that AI can strengthen public health systems and transform medical logistics.
AI can, for instance, supplement the ongoing worldwide efforts to improve immunization logistics and ensure adequate supply of vaccines for children at every local health centre. It can also address many other issues that surround the vaccine cold chain; for instance, the challenge of storing the vaccines at the right temperature in fully operational refrigerators. AI can open ways to improve every aspect of logistics, from transport to storage. Effective application of AI, however, is possible only if the intervening organizations are armed with a combination of relevant government data and advanced AI analytics.
Over the years, there have been significant advancements in AI, which have increased its potential to apply computational game theory, machine learning, automated planning, and multi-agent reasoning techniques to socially relevant problems. But, without proper data, it is impossible to analyse a social crisis. The primary reason for the lack, or absence, of relevant data in most cases is that the population in those areas does not have online presence. Moreover, unlike hospitals in developed areas, the local health centres in remote villages usually have a limit on everything, even data.
India, to its credit, has undertaken great efforts to collect and record information about vaccines and the quality of the cold chains used to store them. The Effective Vaccine Management system deployed in several states, including Bihar and Uttar Pradesh, captures real-time data on not only the availability of the vaccines, but also on the condition of the refrigerators, including a continuous record of temperature. What’s remarkable is that this data covers even the most remote locations in these states. Information of this type can be processed and examined using predictive analysis to forecast stock-outs of vaccines and to optimize the supply chain. Using AI algorithms, the temperature curves of refrigerators can be monitored on a minute-by-minute basis. This can help in predicting failures before they occur.
Another area of healthcare that can benefit greatly from AI is that of human milk banks. Many programs are working towards developing the human milk banking system in India, but, like with vaccines, there are issues concerning the availability and quality of milk. AI analytics, coupled with relevant data, can help detect the regions in which milk banks are needed. Furthermore, it can ensure better quality control and improve distribution efficiency.
The biggest challenge, possibly, for AI in a country like India is to see whether it can be successfully used to eradicate certain infectious diseases. The near-eradication of polio is a worldwide success, including in India, which has now been polio-free for decades. The eradication of a disease happens in two phases. The first involves controlling the disease and reducing the number of cases. The second phase, which focuses on eliminating the disease by tracking down the underlying source of each infection, is a highly data-intensive process. And this is where AI can make a huge difference.
Curing the final cases of a disease requires one to track the households of infected people. This requires a lot of high-quality data to carry out effective predictive analysis, which can then be used to identify the afflicted areas, and accordingly streamline precautionary measures. Malaria has been controlled substantially in many areas, using this approach. AI analytics can also make a huge difference in the control and eradication of parasitic diseases such as dengue and chikungunya, which affect many people in tropical countries but haven’t seen much investment for a cure.
The applications of AI in healthcare are boundless, and healthcare, in turn, is one of the numerous areas where AI can have a significant impact. AI has the potential to address several other matters of national or global concern.
Take agriculture, for instance. The farming models and techniques used in many parts of India are outdated, inefficient, and highly dependent on weather conditions. AI can process satellite photos to arrive at an estimate of the population, weather, crops and existing farming techniques. Analysing this data can help devise good farming models based on environmental conditions and enable farmers to make optimal use of their resources. Unlike in the case of diseases, AI may not be able to completely solve the problem, but it can certainly help us mitigate it.
Since data is the most essential element in the application of AI for societal welfare, it becomes necessary to collect comprehensive data on all those issues that we need to address. There are many ways of doing this, and many more are being discovered. Observing satellite data in the night, for instance, gives an accurate measure of economic activity. Many companies are engaged in developing low-cost sensors that can be distributed among farmers. These sensors can collect data on rainfall patterns over long periods of time. Drone cameras and helium balloons can capture images of a farm to help with assessing the crop yield.
The innovative new ways in which data is collected, coupled with the expanding range of AI applications, augur well for the future of our society. It will be fascinating to watch, in the years ahead, how we use artificial intelligence to overcome real-life problems.
Richard Anderson is professor, department of computer science and engineering, at University of Washington. Comments are welcome at email@example.com.
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