The problem with the world today is that there is simply too much data — and it is only going to get worse. Everyday, different technologies create different types of data. Every button clicked, word typed and information uploaded is a piece of datum created and stored somewhere, waiting to be made use of. It is estimated that today 2MB of data is generated every second for every human on the planet solely across different platforms that touch a lot of aspects of a human"s life. Data from administration systems, social media usage, or even Internet of Things installed in cars and wearables. That’s a lot of data. Imagine what will happen when we have more wearables and devices powered by the Internet of Things all generating data each second. This data tsunami creates a real challenge of trying to figure out how to process all this data to make informed decisions. Which datasets do we mine in order to provide actionable insights? To help sift through the monumental mountain of data it hosts, Saudi Arabia’s National Information Center has set-up an initiative called Estishraf to provide decision support to various Saudi government organizations so policy decisions that affect the lives of citizens consider both human and data-driven perspectives. Estishraf’s role is to identify the correct datasets from the vast pool of data available to generate insights. While Estishraf is a proof of concept for using advanced data analytics to help answer real life questions asked by government officials and decision makers, there are still many questions by other users that remain unasked and unanswered. A solution to this data conundrum can be found in the health and wellness sector. Users today have so many commercial options when it comes to tracking personal performance data with heart rate monitors no larger than the size of a ring, and watches with electrocardiogram monitoring. Soon wearable devices will accurately track blood sugar levels or even blood pressure without the usual pinpricking, and there will be no need to wear a device at all to measure vital signs with your loved ones or your physician being notified if there is a health crisis. How is this possible at scale? There simply aren’t enough doctors in the world to process all this medical data and act upon it. This is where the true value of artificial intelligence (AI) and machine learning (ML) will have an impact on prolonging our lives and detecting ailments early. AI and ML can process data when we don’t have time or resources and recommend or take action. This will make doctors more efficient with artificial intelligence making an initial diagnosis but your doctor being called when there is the first sign of unusual symptoms coupled with a solid patient history. There’s a startup called Cardiogram that is specifically working to make the Apple watch heart rate tracker data more actionable. It has achieved 97% accuracy, 98% sensitivity, and 90.2% specificity with neural networks detecting heart rate anomalies and discovering atrial fibrillation. Why does this matter? Because as more and more people use health trackers, and as the sensitivity and range of these sensors increases, more health data will be shareable with consent with the right health authorities. Advances in medicine will continue at a faster rate, and more importantly, people will be healthier because they have actionable information about their health at an early stage. A watch reminding you that you only took 1,000 steps today is only the first step. Soon, you will have your online AI-based medical assistant to process large amounts of your health data and make weekly recommendations about steps to take, and even schedule visits with your family doctor if needed and present him with all your data prior to your visit. To discuss similar topics on AI for the good of humanity, Saudi Arabia is hosting the Global AI Summit on Sept. 14-15 to unite the world’s policymakers, industry leaders and researchers to forge the future of AI. — The writer is General Supervisor of the Estishraf program, and a specialist in the use of data technologies and artificial intelligence in the National Information Center