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 were
• 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
The project demonstrated how cloud technologies and Artificial Intelligence can transform the current public policy development, increasing automation and efficiency, enhancing and promoting stakeholders’ participation, increasing policies’ acceptance and enabling reuse and interoperability among different context and countries.
The recent significative advancements in the field of LLM and generative AI open a great opportunity to foster the adoption of the AI in the public sector, because they enable a more user-friendly approach for non-technical people, especially for the explainability of the outcomes provided by AI tools.
In the same way, the introduction of the AI Act, providing the needed regulation and guidelines, is of great importance for guaranteeing an ethical use of the AI, especially in the public sector.
These will be two of the main pillars for the new researches and projects that will be activated from the AI4PublicPolicy Consortium for the exploitation of the project’s results.
