Periodic Reporting for period 1 - AI4PublicPolicy (Automated, Transparent Citizen-Centric Public Policy Making based on Trusted Artificial Intelligence)
Berichtszeitraum: 2021-03-01 bis 2022-02-28
The on-going transition of public services towards the Cloud is providing opportunities for increased use by the general public (e.g. through the ubiquitous access advantage of clouds), cost reductions and improved economies of scale, as it is reducing the time needed to develop and roll out new services for the administration and citizens. What is more, cloud computing enables public authorities to harvest the vast amounts of data that they regularly collect and generate, including data from governmental databases and interactions with the citizens, data from public infrastructures (e.g. smart city sensors), as well as data from alternative sources such as social networks and the public internet.
In this context, policy development represents one of the most prominent applications of cloud computing and HPC for public administrations at the local, regional and national levels. Leveraging on large amount of multi-source and multimodal data, public authorities can develop evidence-based, data-driven policies, which aim at being more efficient given that they account for multiple (combined) datasets. Data driven policies can better embrace the needs of the citizens and the administration, in addition to international best practices and past lessons learnt. The ultimate vision of data-driven policy making entails the use of Artificial Intelligence (AI) as a means of increasing the efficiency of the policy development and management process and boosting a more responsive, adaptive, intelligent and citizen-centric governance.
Covid19 Outbreak is a paramount "lesson learned" about how a data-driven approach is crucial for managing critical situation with short responses and fast adaptation and demonstrate why it's important for the Society improving the state-of-the-art data-driven, evidence-based policy making (taking advantage of AI tools and techniques providing predictive models), promoting and facilitating the sharing of datasets and models, involving the citizens in the decision process and explaining the rationales that drive a policy in order to reach the maximum impact and consensus.
The overall objectives of the project are
• Provide reference models and processes for automated, transparent, citizen centric policy management based on AI technologies
• Increase automation and efficiency in policy development through AI-based tools for policy modelling, development, simulation and recommendations
• Repurpose, reuse and link AI-based policies and datasets across various domains and data subjects
• Ensure transparent, interpretable and trusted policy development
• Ensure citizen centric and business centric policy developments, evaluation and optimization
• Provide high performances through the integration with EOSC/EGI cloud & HPC resources
• Validate and evaluate the novel AI-based policy making process in real-life use cases addressing different policy related domains
• Provide a pan-european market platform supported by novel business models for ai-based policy making
In this context, policy development represents one of the most prominent applications of cloud computing and HPC for public administrations at the local, regional and national levels. Leveraging on large amount of multi-source and multimodal data, public authorities can develop evidence-based, data-driven policies, which aim at being more efficient given that they account for multiple (combined) datasets. Data driven policies can better embrace the needs of the citizens and the administration, in addition to international best practices and past lessons learnt. The ultimate vision of data-driven policy making entails the use of Artificial Intelligence (AI) as a means of increasing the efficiency of the policy development and management process and boosting a more responsive, adaptive, intelligent and citizen-centric governance.
Covid19 Outbreak is a paramount "lesson learned" about how a data-driven approach is crucial for managing critical situation with short responses and fast adaptation and demonstrate why it's important for the Society improving the state-of-the-art data-driven, evidence-based policy making (taking advantage of AI tools and techniques providing predictive models), promoting and facilitating the sharing of datasets and models, involving the citizens in the decision process and explaining the rationales that drive a policy in order to reach the maximum impact and consensus.
The overall objectives of the project are
• Provide reference models and processes for automated, transparent, citizen centric policy management based on AI technologies
• Increase automation and efficiency in policy development through AI-based tools for policy modelling, development, simulation and recommendations
• Repurpose, reuse and link AI-based policies and datasets across various domains and data subjects
• Ensure transparent, interpretable and trusted policy development
• Ensure citizen centric and business centric policy developments, evaluation and optimization
• Provide high performances through the integration with EOSC/EGI cloud & HPC resources
• Validate and evaluate the novel AI-based policy making process in real-life use cases addressing different policy related domains
• Provide a pan-european market platform supported by novel business models for ai-based policy making
During the first twelve months of the project (M1-M12), i.e. the first reporting period, the first phase “Specification & Fine Tuning of the AI4PublicPolicy Concept” has been completed and the second phase “Initial Integration & Technical Validation” has been just started. Specifically, the project has advanced in the following areas:
● The setup of collaboration tools and processes
● The creation of the visual identity (logo, templates, website, social media, …)
● The dissemination and contributions to clusters and associations
● The implementation of the co-creation workshops to engage relevant Pilots’ stakeholders in gathering business requirements
● The specification of business requirements, in the form of use cases and user stories that will drive the project’s developments.
● The specification of a common data model for the datasets to be utilized for the development, training and actual utilization of the AI models and algorithms
● The specification of the Reference Model, a first version of the Reference Architecture and a first version of the Organizational Transformation Blueprints driving the technical activities
● The setup of the “Requirements and Innovation tracker”, fed with business and technical requirements, to drive and monitor the development phase
● The implementation of initial Proof-of-Concept demonstrations for the AI-Based Policy Making process, implementing real life and practical scenarios of the Pilot’s use cases
● The setup of collaboration tools and processes
● The creation of the visual identity (logo, templates, website, social media, …)
● The dissemination and contributions to clusters and associations
● The implementation of the co-creation workshops to engage relevant Pilots’ stakeholders in gathering business requirements
● The specification of business requirements, in the form of use cases and user stories that will drive the project’s developments.
● The specification of a common data model for the datasets to be utilized for the development, training and actual utilization of the AI models and algorithms
● The specification of the Reference Model, a first version of the Reference Architecture and a first version of the Organizational Transformation Blueprints driving the technical activities
● The setup of the “Requirements and Innovation tracker”, fed with business and technical requirements, to drive and monitor the development phase
● The implementation of initial Proof-of-Concept demonstrations for the AI-Based Policy Making process, implementing real life and practical scenarios of the Pilot’s use cases
The project will leverage, advance and improve the state-of-the-art data-driven policy making by focusing not only on the insights provided by data, but also on the processing ability and the way to extract and analyze these insights.
Morevover the project will provide the means for optimizing policies based on evidences and citizens’ opinions, while also linking diverse and interoperable policies in order to enhance the repurposing and reusing of them.
AI4PublicPolicy’s proposed approach will combine integrated modelling with knowledge management and visual analytics in order to provide an end-to-end reference model that will embrace the principles of open innovation and social innovation, following a participative approach where all stakeholders contribute in the design and implementation of the public policies.
Several AI Tools will be integrated for obtaining and exploiting citizens’ feedback in a scalable way, which will be one of the main novelties to evidence based policy development, and different XAI techniques will be developed and validated in order to produce more explainable AI models and reveal the main features that drive the decision making, providing policy makers with the ability to intellectually understand the context and the circumstances under which these policies have been created.
Furthermore both semantic and organizational interoperability issues will be targeted, trying to cover both technological and organizational aspects by providing a holistic reference model and produce various blueprints for organizational transformation.
AI4PublicPolicy will enable the policy makers to develop more effective and targeted policies in various areas that are very vital to the citizen’s quality of life and wellbeing, increasing operational efficiency and effectiveness, free employees of repetitive tasks, uncover and extract new data insights and knowledge.
Moreover, the emphasis in the collection and analysis of citizens’ feedback will boost citizens’ participation in the policy development processes, while at the same time boosting civic engagement and increasing the social capital of cities and other citizens groups.
Finally, AI4PublicPolicy will have also a significant ethical impact through providing technological solutions and complementary non-technical assets that will boost the ethical nature of the policy development process.
Morevover the project will provide the means for optimizing policies based on evidences and citizens’ opinions, while also linking diverse and interoperable policies in order to enhance the repurposing and reusing of them.
AI4PublicPolicy’s proposed approach will combine integrated modelling with knowledge management and visual analytics in order to provide an end-to-end reference model that will embrace the principles of open innovation and social innovation, following a participative approach where all stakeholders contribute in the design and implementation of the public policies.
Several AI Tools will be integrated for obtaining and exploiting citizens’ feedback in a scalable way, which will be one of the main novelties to evidence based policy development, and different XAI techniques will be developed and validated in order to produce more explainable AI models and reveal the main features that drive the decision making, providing policy makers with the ability to intellectually understand the context and the circumstances under which these policies have been created.
Furthermore both semantic and organizational interoperability issues will be targeted, trying to cover both technological and organizational aspects by providing a holistic reference model and produce various blueprints for organizational transformation.
AI4PublicPolicy will enable the policy makers to develop more effective and targeted policies in various areas that are very vital to the citizen’s quality of life and wellbeing, increasing operational efficiency and effectiveness, free employees of repetitive tasks, uncover and extract new data insights and knowledge.
Moreover, the emphasis in the collection and analysis of citizens’ feedback will boost citizens’ participation in the policy development processes, while at the same time boosting civic engagement and increasing the social capital of cities and other citizens groups.
Finally, AI4PublicPolicy will have also a significant ethical impact through providing technological solutions and complementary non-technical assets that will boost the ethical nature of the policy development process.