AI4PublicPolicy / Methodology

AI4PublicPolicy will implement and validate a novel AI-based Virtualized Policy Management Environment (VPME) that will enable policy makers to use AI for the development of evidence-based policies. The AI4PublicPolicy implementation processes includes three different phases as analysed below;

 

Phase 1: Specification & Fine Tuning of the AI4PublicPolicy Concept (M1-M9)

  • Collection of insights through user studies of public authorities and policy making stakeholders, and review of reference scenarios for evidence-based policy development. 
  • Analysis of the state-of-the-art in the main technical areas of the project to ensure up to date research outcomes, complemented by information from linked initiatives, relevant standards, applicable regulations, and project-specific requirements. 
  • Recording of the resulting knowledge in reports and analysis through requirements engineering techniques, to create a set of requirements and “innovation forms”, each split into a set of prioritized functionalities to articulate, fine-tune and specify the project in detail. 
  • Specification of the reference architecture and organizational transformation blueprints for AI-based policy development to drive developments in technological WPs and specify the AI4PublicPolicy Requirements and Innovation tracker.

 

Phase 2: Initial Integration & Technical Validation (M10-M24) 

  • Development of initial proof-of-concept (PoC) (i.e. Minimum Viable Products – MVP) prototypes of the project’s solutions to enable secure and safe AI policy development. 
  • Testing of the PoC/MVP of the pilot systems and use cases based on the initial releases of the VPME and the AI tools of the project. All the PoC/MVP prototypes will be tested in the pilot sites of the consortium based on real-life datasets and policy making use cases, as well as the involvement of policy makers. 
  • Production of the initial version of the project’s (i) Semantic interoperability for policies and datasets, (ii) Transparent and Trustworthy AI solutions, and (iii) AI tools for policy making and citizen centric optimization. 
  • Integration of the first version of the reference implementation of the VPME, to drive the first implementation of the project’s pilots and use cases. 

 

Phase 3: Technical & Business Validation (M24-M36)

  • Revision of the MVP prototypes through (a) functionality enhancements with advanced versions of the algorithms and components that support their operation and (b) fine-tuning of the prototypes based on stakeholders’ feedback. 
  • Production of the second version of the prototypes of the solutions, which will enable the production of the second integrated version of the project’s VPME platform, followed by the second cycle of pilot deployments and operations. 
  • An initial business and socio-economic validation based on additional user studies and in conjunction with the project’s business modelling activities.

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