AI4PublicPolicy / The Project

The AI4PublicPolicy Project

AI4PublicPolicy is a joint effort of policy makers and Cloud/AI experts to unveil AI’s potential for automated, transparent and citizen-centric development of public policies. To this end, the project will deliver, validate, demonstrate and promote a novel open cloud platform, the AI4PublicPolicy Platform, for automated, scalable, transparent and citizen-centric policy management based on unique AI technologies.

The AI4PublicPolicy platform will be an Open Virtualized Policy Management Environment (VPME) that will provide fully-fledged policy development/management functionalities based on AI technologies such as Machine Learning (ML), Deep Learning (DL), NLP and chatbots, while leveraging citizens’ participation and feedback. It will support the entire policy development lifecycle, based on technologies for the extraction, simulation, evaluation and optimization of interoperable and reusable public policies, with emphasis on citizen-centric policies development and optimization through the realization of citizen-oriented feedback loops. AI4PublicPolicy will complement public policy development functionalities with the ever-important process reengineering and organization transformation activities towards ensuring the effective transition from legacy policy development models to emerging AI-based policymaking. The AI4PublicPolicy VPME will be integrated with EOSC with a dual objective. First to facilitate access to the Cloud and HPC resources of EOSC/EGI that are 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 commercializing 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.

Why AI4PublicPolicy

Why AI4PublicPolicy

Policy development represents one of the most prominent applications of cloud computing and HPC for public administrations at local, regional and national levels, for harvesting vast amounts of data, including governmental databases and interactions with the citizens, data from public infrastructures, as well as from alternative sources such as social networks and the public internet, while improving the scalability, cost-efficiency, flexibility and quality of public services.

The use of AI-based solutions for data-driven policymaking can adddress technical and organisational challenges such as:

  • Access to Cloud and HPC resources: Scalable infrastructures for storing and analysing datasets are not readily available within public authorities.
  • Transparency: Several AI systems operate as “black-boxes”, making their use challenging, since policymaking must be transparent in terms of the rationale behind the proposed policies and the factual data that drive policy developments. 
  • Trustworthiness: AI systems for policymaking must be secure, safe and resilient against malicious attempts, as well as address the ethical AI challenges (as analysed by EU’s High-Level Expert Group (HLEG) on Artificial Intelligence).
  • End-to-End Integration: AI’s potential in policymaking is significantly underexploited, given it provides opportunities for automating and supporting policymaking activities, including front office, middle office, and back-office activities.
  • Organizational Transformation: The introduction of AI systems in policymaking leads to automation and efficiency, yet it challenges peoples’ roles and responsibilities, requiring significant upskilling and reskilling for policy making experts and other employees of the public administration.

To this end, AI4PublicPolicy will deliver, validate, demonstrate 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 AI4PublicPolicy platform will be an Open Virtualized Policy Management Environment (VPME) that will provide fully-fledged policy development/management functionalities based on AI technologies such as Machine Learning (ML), Deep Learning (DL), NLP and chatbots, while leveraging citizens’ participation and feedback. It will support the entire policy development lifecycle, based on technologies for the extraction, simulation, evaluation and optimization of interoperable and reusable public policies, with emphasis on citizen-centric policies development and optimization through the realization of citizen-oriented feedback loops. AI4PublicPolicy will complement public policy development functionalities with the ever-important process reengineering and organization transformation activities towards ensuring the effective transition from legacy policy development models to emerging AI-based policymaking. The AI4PublicPolicy VPME will be integrated with EOSC with a dual objective. First to facilitate access to the Cloud and HPC resources of EOSC/EGI that are 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 commercializing 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.

Outcomes

Project Outcomes

AI4PublicPolicy will complement public policy development functionalities and ensure the effective transition from legacy policy development models to emerging AI-based policymaking by addressing 8 macro-objectives, tracked through key indicators as follows;

1. Specifications of reference models and processes for automated, transparent, citizen centric policy management based on AI technologies.

  • Number of AI tools for policymaking 
  • VPME Reference Architecture
  • Organizational Transformation Blueprint

2. Increased automation and efficiency in policy development through AI-based tools for policy modelling, development, simulation and recommendations tools.

  • Reduced time to model and develop a policy model
  • Reduced time to benchmark and compare alternative policies

3. Repurpose, reuse and link AI-based policies and datasets across various domains and data subjects.

  • Ontologies and Taxonomies to be reviewed for specifying the AI4PublicPolicy Ontologies
  • Number of Ontologies and Archetypes to be produced
  • Number of Policies to be reused across organizations in the AI4PublicPolicy market platform
  • Policy Linking Tool

4. Transparent, interpretable and trusted policy development.

  • Number of XAI algorithms/techniques to be introduced and validated 
  • Policy Interpretation tool
  • Cyber-security / Cyber-defence Techniques for AI Systems to be Implemented (Evasion, Poisoning)

5. Citizen-centric and business-centric policy developments, evaluation and optimization.

  • Artificial Intelligence (AI) tools for citizens interaction and feedback 
  • Policy optimization models and algorithms

6. High-performance integrated AI-based policy management based VPME’s integration with EOSC/EGI cloud & HPC resources.

  • AI models deployed over the European Cloud Initiative and infrastructure (EOSC)
  • Virtualized Policy Management Environment integrated with EOSC 
  • Stakeholders accessing the EOSC/EGI-based Virtualized Policy Management Environment

7. Validation and evaluation in real-life use cases addressing different policy-related domains.

  • Pilot systems to be integrated and deployed
  • Policy Development Use Cases to be Integrated
  • Policy Makers (individuals) to be engaged in the pilots
  • Policy Making Stakeholders engaged in the CoCreation Processes 
  • Tools repurposed and reused across scenarios and use cases

8. Pan-European market platform supported by novel business models for AI-based policymaking.

  • Policy Makers Registered in the Market Platform 
  • Public Organizations Registered in the Market platform 
  • Training programs available in the market platform
  • Policy Making Datasets in the Market Platform
  • AI algorithms in the market platform
  • AI tools for policy making in the market platform
Workplan

Workplan

AI4PublicPolicy will be implemented based on a three-year workplan, structured in 8 work packages:

  • WP1 includes all the project management activities i.e. project, technical, risk, quality and innovation management. It also includes the ethical and legal analysis activities. 
  • WP2 is devoted to producing key specifications for the project’s AI-based policy-making paradigm, while including the user studies and the co-creation activities. WP2 will drive all the technical development work packages of the project and have a two-way interaction with the pilot tasks; 
    • provide requirements for integrating and operating the pilot systems, 
    • receive feedback from the pilot systems regarding the specifications of the AI technologies and VPME of the project. 
  • WP3, WP4, WP5 are the core technical work packages of the project, which focus on three independent, yet complementary streams of technological work; 
    • policy interoperability and reuse technologies, including ontologies, archetypes, ontology engineering tools and policy linking techniques;
    • technologies and tools that boost the trustworthiness of the policy development process, including XAI tools, AI cyber defence techniques and technologies for secure data sharing of policy models and datasets across stakeholders;
    • integration of the VPME and the project’s AI tools within an open analytics environment (e.g., KNIME). 
  • WP6 is the pilot’s work-package that will be devoted to deploying, operating, validating and evaluating the pilot systems with the active engagement of the public authorities of the consortium. 
  • WP7 will provide inputs to the co-creation sessions in WP2 and to the pilot operations (WP6), as the training and organizations transformation blueprints of the marketplace will be used in the pilots and in the co-creation. 
  • WP8 is the dissemination, communication, exploitation and standardization work-package of the project.

The below figure illustrates the project’s workplan.

Methodology

Methodology

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.
The Virtualised Policy Management Environment

The VPME

The AI4PublicPolicy Platform will be an Open Virtualized Policy Management Environment (VPME) that will provide fully-fledged policy development/management functionalities based on AI technologies such as Machine Learning (ML), Deep Learning (DL), NLP and chatbots while leveraging citizens’ participation and feedback. It will support the entire policy development lifecycle, based on technologies for the extraction, simulation, evaluation and optimization of interoperable and reusable public policies, with emphasis on citizen-centric policies development and optimization through the realization of citizen-oriented feedback loops. AI4PublicPolicy will complement public policy development functionalities with the ever-important process reengineering and organization transformation activities towards ensuring the effective transition from legacy policy development models to emerging AI-based policy making.

The AI4PublicPolicy VPME will be integrated with EOSC with a dual objective. First to facilitate access to the Cloud and HPC resources of EOSC/EGI that are required to enable the project’s AI tools, second to boost the sustainability and wider use of the project’s developments. AI4PublicPolicy’s business plan for sustaining, expanding and commercializing 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 policy makers) around the project’s platform.

The project’s Virtual Policy Making Environment (VPME) will integrate various tools and will support policy makers to address policy development challenges based on leading edge AI technologies. Specially, the VPME will enable:

  1. Automated, Scalable and Effective Data-driven Policy Making
  2. Citizens, Businesses and Policy Makers Feedback, Interaction and Optimization
  3. Repurposing, Reuse and Linking of Policies and Datasets
  4. Trusted, Transparent and Ethical AI for Policy Making
  5. Public Authorities Transformation

No Comments

Sorry, the comment form is closed at this time.