Towards the Improvement of Citizen Communication Through Computational Intelligence

When dealing with problems that arise from collective sharing of resources in metropolitan areas (i.e., energy, pollution, traffic, health) most of the interaction between citizens and local governance is usually carried out through the use of natural languages. Digital technologies allows smart cities residents to communicate with a broad range of experts (e.g. bureaucrats, legislators, urbanists, etc.) that routinely use technical terminology seldom accessible to the layperson, or linguistic styles that are not immediately understandable. Although information technology should encourage citizen participation in governance at many levels, the different levels of knowledge possessed by the actors can lead to incomprehension, as well as social exclusion. Computational Intelligence approaches can be used in order to alleviate such difficulties and improve the efficiency of communication through automation and collective cognitive systems. In this paper we discuss how use of techniques such as CWW and Fuzzy Classifiers can be beneficial toward the reduction of the communication gap between citizens and government