AI AND MACHINE LEARNING TO IMPROVE EVIDENCE-BASED DECISION-MAKING

The Córdoba City’s Municipality, through the Smart City and Digital Transformation Secretary, fosters an approach based on the modernization of the State and, through the implementation of various systems, creates vast amounts of data that allows for the analysis of the evolution and impact of different programs and public policies. However, some of this data is fragmented across several databases which are not properly standardized or structured or the information is not currently digitised. This limits administrative capacity to identify patterns, anticipate needs and evaluate programs’ impact accurately with the goal of improving decision-making processes. 

In this context, a solution is required to optimize data collection and analysis for evidence-based decision-making. This solution should include, at least: 

• Integration of different data sources;

• AI and machine learning implementation to identify tendencies, predict public services demand and make strategic recommendations;

• Generate a control dashboard and reports;

• Guarantee safe access and data governance in compliance with regulations for information and data protection and privacy.

Specifically, there is a need to establish an intelligent urban complaint prioritization system that, based on the information generated by the various complaint reception channels, allows for the analysis of the criticality of each complaint according to: type of complaint, geographical location, recurrence, grouping, and social impact. In this way, information could be collected from various citizen service channels, processed based on criticality parameters, and prioritized lines of action obtained.