AI4PublicPolicy comes to an end
The AI4PublicPolicy project
The AI4PublicPolicy project is a joint effort of policymakers and Cloud/AI experts to unveil AI's potential for automated, transparent and citizen-centric development of public policies. To this end, the project goal were to deliver, validate, demonstrates and promote a novel Open Cloud platform (i.e. AI4PublicPolicy platform) for automated, scalable, transparent and citizen-centric policy management based on unique AI technologies. The AI4PbulicPolicy platform is an open Virtualized Policy Management Environment (VPME) that provides Deep Learning (DL), NLP and chatbots, while leveraging citizens' participation and feedback. It supports the entire policy development lifecycle, based on technologies for the extraction, simulation, evaluation and optimization of interoperable and reusable public feedback loops. AI4PublicPolicy complements public policy development functionalities with the ever-important process reengineering and organisation transformation activities towards ensuring the effective transition from legacy policy development models to emerging AI-based policymaking.
Main results
The VPME has been personalised for the different pilots of the project to allow them to analyse and improve the policy relating to different aspects of the public administration. In particular:
- Athens, Greece - Led by City of Athens IT Company (DAEM)
- The pilot aimed at developing, demonstrating and evaluating data-driven, citizen-centric and evidence-based policies about the maintenance of the city’s infrastructure and the citizens’ transport and urban mobility, including the economic implications of these policies.
- Genoa, Italy - Led by City of Genoa (CDG)
- The pilot integrated various AI tools, including tools for analysing citizens’ feedback, but mainly tools for data-driven policy recommendation, policy simulation and bench-marking. Based on this tool, the pilot system extracted and recommended policies for allocating resources and organising the operations of the different departments of the municipality.
- Lisbon, Portugal - Led by Lisboa E-Nova (LIS)
- The pilot focused on gathering relevant and valid data sources, such as weather, buildings’ characteristics and energy consumption, and with the aid of AI and machine learning algorithms detect patterns and problems regarding energy efficiency, so that possible data-driven policies can be defined to ensure a more sustainable and efficient environment in the city.
- Burgas, Bulgaria - Led by Burgas Municipality (BURGAS)
- The pilot developed a policy making tool that creates and evaluates alternative water pipes maintenance plans, based on data-driven insights about the water management infrastructure (e.g., information about pipes’ installation, placement, and maintenance) and its operative condition.
Holistic and Accessible Urban Mobility
- Nicosia, Cyprus - Led by Nicosia Municipality (NIC)
- The pilot tested a system for energy management policies. The work involved the tailoring and customization of the AI4PublicPolicy platform and tools.
EGI's contribution
The AI4PublicPolicy VPME is integrated with EOSC with a dual objective. First to facilitate access to the Cloud that is required to enable the project's AI tools, and second to boost the sustainability and wider use of the project's developments. AI4PublicPolicy's business plan for sustaining, expanding and commercialising the AI tools and the VPME is based on the development of a community of interested and engaged stakeholders (i.e. public authorities and other policymakers) around the project's platform. EGI has participated in the project on the provisioning of the Cloud infrastructure and the services used to build both the VPME and the AI4PublicPolicy Marketplace. In particular it exploited:
Furthermore EGI effort has been devoted to the development of the exploitation plan that contributes to the future plans as well.
Future plans
The project has completed the release of the planned VPME and released a document with the exploitation plans including the overall joint approach to the results exploitation, the partners` individual exploitation plans describing their intentions for exploitation of AI4PublicPolicy outcomes, and the progress on the planned actions.
This includes plans for KEA and VPME exploitation after the end of the project, with a detailed strategy about cost, maintenance and replicability for the next three years. The result is a definition of possible routes towards the future exploitation and commercialization of the assets and platform, as well as defining the exploitation strategy, channels and paths, with a conclusive mapping of IPR and structured joint exploitation of VPME.
