As Artificial Intelligence offered its best at the beginning of the pandemic, starting from predicting the outbreak up to monitoring the number of cases, it continues to facilitate all our life aspects for us and our children to be able to work, study, and play safely. Virtual assistants and chatbots have been deployed to support healthcare organisations. The US Center for Disease Control and Prevention and Microsoft have developed a coronavirus self-checker service to help users self-assess COVID-19 and suggest a course of action. AI has been used for checking temperature using; tracking cases and their contacts with facial recognition and smartphones; and tracking the GPS location and itinerary of infected people through mobile phones. You no longer need to physically perform your tasks as AI gives you the ability to control your home or company remotely.
There are more mobile phones than humans on earth. That presents a unique opportunity for big data and, more importantly, the insights from the data to be applied to greater social good. At this week's PAPIs Connect--a predictive application programming interface (API) conference in Valencia, Spain--Nuria Oliver, the scientific director of Telefonica's R&D program, spoke about how to adapt this data via machine learning. Today, we touch on two of the situations she presented where big data and machine learning gave insight into how governments can better address crises, whether it's a natural disaster or a disease outbreak. In this piece we aren't talking about personalized data or even that which we're offering via our social media accounts.
The developing regions of the world contain most of the human population and the planet's natural resources, and hence are particularly important to the study of sustainability. Despite some difficult problems in such places, a period of enormous technology-driven change has created new opportunities to address poor management of resources and improve human well-being.