Challenges in Truly Scaling Services

Abstract

Many services, such as healthcare and education are highly human-intensive offerings that remain inaccessible (at acceptable quality level) to large numbers of people. With advances in computational power and increasing digitization of the world, there is an opportunity to apply data analytics to transform these services. This talk will describe opportunities and key challenges, both algorithmic and performance-related, to achieve truly transformational impact. We begin by describing a dire need and an opportunity to improve the healthcare system worldwide by supporting a shift from reactive treatment to more proactive action. As examples of what is possible, we present techniques to predict a class of complications in an ICU, to identify patients in a hospital who are likely to require ICU admission, and measure body vitals through remote sensing at home or workplace for wellness or to screen for diseases and reduce the need for people to visit a hospital. We then describe a system called TutorSpace to help with personalization and improved navigation of videos from massive open online courses to enable more effective learning. We describe some of the performance issues we have faced to make these systems practical, and our approach to those problems. We frame all of the above efforts as examples of using information technology to offer personalized services at massive scale.