Cecilia Cabello is the Director of Operations in the Spanish Foundation for Science and Technology, FECYT, an institution dependent on the Spanish Ministry of Science and Innovation. Cecilia is the Project Coordinator of IntelComp, a H2020 project where OpenAIRE is a partner, that delivers innovative big data, AI-driven methods for policy making in the Research and Innovation sector.
IntelComp sets out to build an innovative Cloud Platform that will offer Artificial Intelligence based services to public administrators and policy makers across Europe for data- and evidence-driven policy design and implementation in the field of Science, Technology and Innovation (STI) policy.
Public administration at all geographical and organisational levels, STI stakeholders and civil society produce a great amount of dynamic, multilingual and heterogeneous data (i.e. national STI strategies, plans and work programmes, calls, projects, reports, scientific publications, patents, dissemination articles, etc.), so understanding and analysing this data is crucial for evidence-based policy making.
STI policy making has evolved in the past decade, and from policies that enabled catch-up growth, we are now progressing towards policies that are more aligned with sustainable development through integrating social, economic and environmental dimensions.
"Policy Intelligence" streamlines a big data, AI-assisted policy modelling approach to improve human judgment for evidence-informed policy making. Advances in computational power (HPC, European Open Science Cloud, commercial clouds), combined with the unprecedented volume and variety of data from the Research & Innovation (R&I) domain, the public sector information (PSI) and the web, have created ideal conditions for the development and application of AI techniques (e.g., Natural Language Processing, Machine Learning, data mining) and modelling approaches to improve the design and implementation of STI policies.
I would highlight, first of all, co-creation. We think that it's very important to co-develop tools and policies. We have established three (3) Living labs on specific themes of high interest to public administration and society: AI, Health and Adaptation to Climate Change. Throughout IntelComp, we will engage public policy makers, academia, industry, SMEs, local actors, civil society and citizens to explore, experiment with and evaluate STI policies at all stages.
Another recommendation for the IntelComp team is co-design. Understanding the challenges of STI policy making via the development of a co-designed framework with stakeholders and citizens is a key element not just for IntelComp, but also for a sustainable policy adoption by the public.
Finally, we would like to stand out the collaboration. We need to be aware that a multidisciplinary approach and a close collaboration among public (academia, government) and private (cloud industry, policy consultants) organisations is needed to develop big data infrastructures and intelligent systems-science modelling approaches that truly address emerging challenges.
The whole world will have to overcome many changes in the next decade to truly realise the potential of AI to improve working and social life. Artificial Intelligence will change our lives by 2030. The proposed AI tools in Intelcomp are state-of-the-art and allow open ended collaborations with research teams across Europe and by introducing big data/AI in the monitoring and evaluation workflows to address these changes.
In terms of challenges, we have many. But two stand out: access to data and training of staff in specialised subjects. The envisioned Data Space of the project will include a wide variety of data sources and corpora. Some of the datasets are open public data, others are not. We have to take in mind the problems raised by big data uses
Today we have access to more opportunities in health, education and development. But Public Sector decision making needs to become more agile, breaking down data silos to combine day-to-day tactical decisions with longer term policies and strategies. For this reason, we recommend attending the event to learn from others. Conducting analyses of large-scale projects allows visualisation of the expected impacts of "potential" change to help make better evidence-based operational decisions and longer-term policy choices. And then for create synergies with other cloud projects through a joint effort of policy makers and Cloud/AI experts.