Keynote Speech 2 How Machine Intelligence Transforms Sabah E-Government to Smart Government

Over the last few years, the concept of e-government has enabled governments to serve the public using the Internet. It also allowed governments to capture data, process and report on data efficiently and improve on their decision making. However, the advances in smart technologies (e.g., Artificial Intelligence and Machine Learning), better informed and connected citizens, and global connected economies have created opportunities, forcing governments to rethink their role in today’s society. With the rise of people awareness about the fourth industrial revolution (IR4.0), driven by four disruptions: the astonishing rise in data volumes, computational power, and connectivity, especially new low-power wide-area networks; the emergence of analytics and business-intelligence capabilities; government should look into a few opportunities to transform from e-government into a modern and smart government. Local governments can now gather real time data, combined with the capabilities of artificial intelligence, and are realizing interesting new ways to run more efficiently and effectively. Artificial Intelligence is a collection of advanced technologies that allows machines to sense, comprehend, act and learn. Some of the key applications include intelligent automation, robotic process automation, cognitive robotics, virtual agents, machine learning and deep learning, natural language processing and video analytics. It was unrealistic to apply artificial intelligence or machine learning to many areas of government administration before. But now even more exciting, machines can now analyze things that humans might not have been able to do so before. In this talk, we will share some of the machine learning algorithms that can now be applied in transforming Sabah e- Government to smart government. Particularly, we will look several applications that can be used to enhance the effectiveness of Sabah administration that include detecting fake news, measuring public opinion using sentiment analysis, learning how people use cities/buildings in order to optimize infrastructures in cities/buildings, improving public safety in cities/buildings and improving services and productivity.