The constant development of Artificial Intelligence (AI) methodologies makes the automation of processes more and more attractive for the Public Administration and Government (PAG). Due to the advances in AI and Information Technology (IT), several PAG processes which, a few years ago, had to be completely carried out by humans can be automated today. The overall PAG domain involves a diversity of application areas in which Intelligent Systems may play a key role in a near future, namely in: Government, Urban Planning, Transports, Traffic Management, Energy, Water and Waste Management, Citizenship, Hospital Management & Public Health, Culture & Heritage Management, Tourism, Education & Research Management, among many others.
To enable the use of Intelligent Systems in these application areas, different AI/IT methods and technologies are needed, such as: Data Science; Analytics; Decision Support Systems; Machine Learning; Optimization; Natural Language Processing; Social Media Analytics; Modeling & Simulation; AI Planning; Agents and Multi-Agent Systems; Social Intelligence; Internet of Things (IoT), Machine Perception, Robotics & Automation; Big Data and Cloud/Edge Computing; User Modelling; Cybersecurity; and Sustainable Computing.
This thematic line aims to address the challenges raised by current trends on innovative electronic service provision, in particular in the field of e-government and public administration. It thus focuses on advanced AI-powered IT solutions to address the relationships between humans and online services, and the use of AI to improve public administration services. In the context of this thematic line, LIACC intends to improve and promote public policies and decision-making processes, making them more data-driven. This will be achieved by using modern IT/AI methodologies, allowing to first collect and integrate the relevant heterogeneous data, generated in Public Administration and other sources (e.g., social media), and then process “intelligently” such data, providing valuable insights and actionable knowledge.