An information day on policy-making and the usage of AI was organised in Brussels on December 14th, 2023, by the EC-funded project IntelComp. The event’s primary goal was to facilitate interaction among people responsible for drawing and shaping policies and those who can analyse and improve the process of policy-making by leveraging new technologies, data and engaging the human factor in the whole policy cycle. After all, all of us, as Europeans, will be directly impacted by those policies. The agenda is set up and split into six sessions. Important Q&As followed after each speaker’s presentation with the expertised audience expressing both arguments and experiences on the new era of policy making and how all Europeans can benefit from their inclusion in the process.

Starting with Mr. Dominique Guellec, it was pointed out that in the ever-evolving landscape of policy-making, the integration of artificial intelligence (AI) emerges as a transformative force, particularly in the intricate domains of Science and Technology (S&T). The demand for informed decisions has grown exponentially, propelled by the escalating size and complexity of S&T activities and the expanding role of governments in addressing societal challenges such as green initiatives, aging of populations, and security concerns. The existing Science, Technology, and Innovation (STI) policy frameworks, encompassing diverse actors and multifaceted goals, underscore the pressing need for policymakers to access more granular, connected, and dynamic information. On the supply side, the convergence of vast digitised data and remarkable advancements in machine learning techniques, from Convolutional Neural Networks (CNN) to Natural Language Processing (NLP) and Generative AI, presents unprecedented opportunities. AI's capabilities encompass quantitative analysis, NLP-driven text analysis, and generative abilities, mirroring human capacities but at a fraction of the cost. However, challenges persist, including biases, hallucinations, and the elusive nature of explainability. The integration of AI in the STI policy cycle, from agenda setting to evaluation, showcases its potential to enhance processes, streamline decision-making, and map impact pathways. Despite the enormous opportunities, there is a call to address challenges through ongoing efforts, emphasising the importance of human involvement in the decision-making loop and the necessity for policymakers to invest in these tools. The future lies in a collaborative synergy between human intelligence and machine capabilities, paving the way for more informed, effective, and forward-thinking policies.

Continuing on the dynamic realm of policy-making, Mr. Arenas noted that IntelComp is charting a new course by seamlessly integrating open scholarly works data with the formidable capabilities of Artificial Intelligence (AI), with the vision to empower policymakers with cutting-edge AI tools, ushering in a paradigm shift towards evidence-based decision-making. The results are groundbreaking, with applications like the IntelComp Catalogue, Graph Explorer, STI Viewer, Policy Participation Portal, and Evaluation Workbench redefining how we aggregate, visualise, and evaluate Science, Technology, and Innovation (STI) data and policies. At the technological forefront, we harness the power of scalable Natural Language Processing (NLP), Neural Machine Translation (NMT), GPU processing, and advanced models like GPT for enhanced interpretability. Looking ahead, IntelComp is committed to maintaining an active platform infrastructure, continuous refinement of web services, and fostering more intuitive interactions. Closing, he invited the audience to embrace the IntelComp initiative on this journey as it pioneers innovation, technology, and a steadfast commitment to shaping evidence-based policies for a brighter future.

Following, panel 1 guest speakers initiated the discussion on the policy making process from funders and policy makers/intermediaries view. Ms. Kouravelou, the director of the Hellenic Foundation for Research and Innovation (HFRI), as a consortium member of IntelComp, talked about AI's Role in Shaping HFRI's Funding Strategy. In navigating the evolving landscape of funding strategies, the IntelComp Platform stands to revolutionise HFRI's approach with the strategic infusion of Artificial Intelligence (AI). Through a meticulous analysis of HFRI's rich data spanning from 2016 to 2023, including Hellenic Research Community interests, demographic data, and a comparative examination with EU and global datasets, AI unveils nuanced patterns and highlights specific Scientific/Thematic Areas deserving attention. Looking forward to the Multiannual Financial Framework (2024 – 2030), AI steps into the spotlight by crafting a dynamic strategy for upcoming calls, tailoring them to emerging needs and topics. Embracing the power of AI, HFRI envisions a future where the platform aids in orchestrating special calls, building on successful initiatives like the 2020 action tackling the socio-economic impacts of the COVID-19 pandemic. The pilot deployment of AI in evaluation and monitoring processes further solidifies IntelComp's commitment, offering seamless integration with HFRI's registry and proposing evaluators and experts to ensure the technical vitality of funded projects. As we embrace this convergence of technology and strategy, IntelComp emerges as a trailblazer, charting a transformative path for HFRI's funding landscape.

Next expertise, Mr. Reid, Policy Director, of the European Future Innovation System (EFIS) Centre, talked about unleashing AI in STI Policy Challenges. In the vast landscape of science, technology, and innovation (STI) policy-making, the fusion of Artificial Intelligence (AI) becomes a beacon of transformative possibilities. Embarking on this AI journey, the first challenge lies in addressing the data availability conundrum for the Regional Innovation Scoreboard. From framework conditions encompassing human resources, attractive research systems, and digitization to investment aspects like finance, support, and firm investments, and further into innovation activities and impacts—AI emerges as the key to streamlining, analysing, and leveraging this wealth of information. The second challenge amplifies the call for AI's prowess in identifying complementarities across inter-regional innovation ecosystems. Thematic smart specialisation partnerships, seeking complementary expertise and resources, currently rely on manual exercises. A question posed is now; Can AI revolutionise this mapping process, delving deeper and broader into potential collaborations to foster inter-regional value chains and innovation networks? Lastly, as EU Missions unfold with multi-level initiatives, the third challenge beckons AI to the forefront. Here, AI holds the potential to navigate the complexities of identifying and mapping networks of actors at various levels, from EU to local, facilitating match-making and partnership-building. Moreover, AI's capacity to track portfolios of actions, investments, and funding instruments stands as a time-saving marvel, offering essential support in managing and assessing contributions to the mission theory of change. In the quest for seamless policy management, the marriage of AI and STI emerges as the catalyst for a future where data becomes a dynamic rather than a daunting challenge.

Mrs. Tsipouri, Economist, Professor, National and Kapodistrian University of Athens, and co-founder of spin-off OPIX, talked about revolutionising RTD Policy with AI-Driven Intelligence: A Paradigm Shift. More specifically, in the realm of policy-making and research, the struggle for pertinent data and insightful analysis has long been a source of agony. "How can the world get rid of consultants?" echoes the plea for a more streamlined approach. Recognizing the insatiable request for data among policy makers, the IntelComp Platform proposes a game-changing solution: AI-driven Policy Intelligence. This visionary platform aims to deliver a comprehensive data ecosystem, tailored to the intricate spectrum of Research, Technology, and Development (RTD) policy. The policy cycle of; Design, Implementation, Monitoring, and Evaluation, spanning seven critical functions, demands a holistic approach. Here, AI steps into the spotlight, not merely as a tool but as a transformative force. Traditional methods, relying on biassed surveys and interviews, have limitations, and aggregated data often falls short of policy makers' expectations. AI, poised to organise data across the time dimensions—Hindsight, Now Sight, and Foresight. This dynamic approach covers Science, Technology, Economic, and Social Impact data, meticulously classified to the lowest level possible, offering both standard and new classifications to unveil hidden issues. Therefore, the delivery mechanism of AI-driven intelligence is equally innovative. From basic knowledge through selected indicators to providing raw data for individual processing, the IntelComp platform empowers users with suggestions and the freedom to experiment. It doesn't stop there—detailed explanations accompany the data, bridging the gap between what, how, and why. Training modules facilitate hands-on experimentation, transforming data into a powerful tool for policy makers. In a landscape grappling with questions and challenges, AI emerges not just as a solution but as the catalyst for a new era in RTD policy-making, paving the way for a more informed and dynamic future.

Lastly, Mr Carsten Schwäbe - Chair of Innovation Management, Researcher, Freie Universität Berlin, focused on nurturing Agility: AI's Role in Transformative Innovation Policy. In the ever-shifting landscape of transformative innovation policy, the demand for agility is imperative, driven by the uncertainties and interdependencies associated with ecological, digital, geopolitical, and demographic transformations, including migration. Weber et al. (2021) propose a multi-dimensional agile Science, Technology, and Innovation (STI) policy, emphasising flexibility, proactivity, participation, ambidexterity, and reflexivity. Here, the integration of Artificial Intelligence (AI) emerges as a potent force, offering both opportunities and considerations. AI holds the promise of enhancing flexibility and proactivity in policy-making, accelerating instrument implementation, coordination, and adaptation. Its capacity to analyse large text-based documents from stakeholders presents an opportunity for organised participation, shedding light on diverse perspectives. Furthermore, AI can replace or create organisational structures, fostering ambidexterity within public organisations and paving the way for mission-oriented innovation policy agencies. In the realm of reflexivity, AI's potential to support monitoring, evaluation processes, and policy learning stands out, providing data-driven insights. However, as we embrace these opportunities, we must acknowledge the limitations. While AI can prepare proactive measures and assist in participatory processes, the core of normative democratic principles, strategic development, and decision-making inherently remains a human endeavour. The intricate choreography between human-AI interaction, uncertainty, and the nuanced political interpretation of results underscores the need for a balanced approach. How do we ensure that as AI contributes to transformative policy, it aligns seamlessly with democratic principles? This nuanced integration of technological innovation and democratic governance will chart the course for policy-making in an era defined by transformative change.

Next panel, panel 2, was focused on the usage of big data and AI in policy making. First speaker was Mr. Papageorgiou, describing the data-driven analysis of EU's Energy and Agri-Food Innovation Landscapes, driven by AI-enabled IntelComp tools. He claimed that in  our pursuit of supporting evidence-based policymaking, we analyse and present dynamic, multilingual, and heterogeneous data for the EU's energy and agrifood sectors. Focusing on key business questions, we delve into the extent to which investments in research and innovation translate into industrial applications, specifically in green technology across EU countries. Our extensive dataset spans technology, industry, policy documents, regulations, human resources, and domain-specific sources. For example, we observe Germany and Italy leading in the number of energy companies, with France standing out in patents and trademarks. Comparing scientific research between industry and academia offers valuable insights, while the analysis of patents and publications reveals distinct trends, showcasing the IntelComp platform's ability to provide nuanced perspectives. In the agrifood sector, we explore technological insights aligned with Sustainable Development Goals (SDGs), agrifood regulations, and the need for environmental protection legislation to catch up with technological advancements. Of course, there is a discussion on the trustworthy AI framework, emphasising guidelines for lawful, ethical, and robust AI deployment, prioritising human control, harm prevention, fairness, and explicability. This data-driven analysis sets the stage for informed policymaking and strategic innovation in the EU's complex energy and agrifood domains.

Another view was presented by Mr. Aristodemou, Policy Analyst, OECD Directorate of Science, Technology and Innovation, Division of Science and Technology Policy. His presentation was on Breaking New Grounds: Unleashing the Power of OECD Fundstat Infrastructure. The OECD Expert Group on the Management and Analysis of R&D and Innovation Administrative Data was established in 2021, and focuses on administrative data surrounding R&D and innovation funding. Serving as a dynamic forum, it facilitates the exchange of practices, challenges, and co-ordinates common approaches among officials managing data within R&D and innovation funding bodies. At the heart of this initiative is the groundbreaking OECD Fundstat Infrastructure, a comprehensive repository comprising government-funded R&D projects from a diverse array of OECD member countries and the EU. With a constant drive for improvement, the Fundstat Infrastructure is expanding its coverage to measure the contribution of science and innovation to the Green Transition. Notably, the infrastructure played a pivotal role in gauging the magnitude of government support for COVID-19 R&D during the pandemic, identifying over 11,886 projects totaling a staggering USD 12.5 billion.  As we look toward the next phase, the OECD Fundstat is poised to enhance its coverage and continue shaping the future of R&D analysis on a global scale.

Next expert, Mr. Di Virgilio, Policy Analyst, European Commission, DG Research & Innovation, talked about the Transforming Policy Landscapes: The Synergy of Disruptive AI and Linked Big Data.  In an era marked by unprecedented challenges—ranging from the climate crisis and geopolitical shifts to the ongoing pandemic and intricate demographic changes—the fusion of Disruptive AI and Linked Big Data emerges as a catalyst for a new culture of evidence-based policymaking. Recognizing the pivotal role of data in informed policy decisions, this transformative approach transcends traditional methodologies. The intersection of AI, research, and policymaking introduces a paradigm shift, presenting solutions to critical issues such as the global chain governance change and the organisational readiness required for data-driven methods. Embracing big data and AI revolutions, the infrastructure, known as TRR methodology, navigates challenges in tracking research results, offering solutions for time efficiency and adapting to the constantly changing policy landscape. As we delve into the lessons learned from this innovative approach, the convergence of policy and data expertise stands out as a prerequisite for acceptance. Big data proves invaluable for extensive project activities, yet the stability of the framework and the necessity for continuous data availability pose pertinent questions. Leveraging TRR methodology to measure impact provides insights into scientific, technological contributions, and the impact on Sustainable Development Goals (SDGs). However, addressing new challenges necessitates a shift in skills and culture, urging a multi-faceted, interlinked data infrastructure for all use cases. In the quest for a harmonised and curated Knowledge Graph repository, the emphasis on upskilling colleagues, bridging gaps between policy and data experts, and fostering a collaborative, multidisciplinary approach becomes paramount. The journey unfolds with a call to stop testing and start tasting, inviting a profound shift towards a future where AI and big data blend seamlessly, empowering evidence-based policymaking with unprecedented precision and agility.

The last panel, panel 3, was focused on the co-design process of policy development, including citizens as end-users in the policy cycle process, and all invited speakers are experts supporters and implementers of this approach. Starting, Mrs Silva, General Manager, Trisolaris Advanced Technologies, talked on Empowering Policy Receptors: A Blueprint for Engagement in AI, Health, and Climate Policy Development. In the dynamic landscape of policy development, the role of policy receptors—citizens, experts, organisations, and affected communities—is pivotal. Their comprehension of policy frameworks, active participation in decision-making, and provision of feedback significantly influence the quality and relevance of policy development. To enhance comprehension, visual aids such as infographics and simplified language are key. Regular updates through accessible communication channels, engagement workshops, and collaborative platforms inform policy receptors about ongoing developments. Actively involving stakeholders through public consultations, forums, and meetings is essential for effective decision-making. Some feedback mechanisms, including online surveys, focus groups, and feedback forms, provide valuable insights. The analysis of this feedback, both quantitative and qualitative, informs policy revisions and improvements. Overcoming engagement barriers requires a commitment to accessible communication, ongoing workshops, and collaborative platforms. Highlighting successful instances and case studies in AI, healthcare, and climate action showcases the positive impact of stakeholder engagement. Encouraging ongoing participation through continuous communication, regular consultations, and recognition of stakeholder contributions reinforces the significance of their involvement in shaping impactful policies.

Mr. Konstantinidis, President of the European Network of Living Labs (ENoLL). Leader of ASOSS Research Group at Medical Physics & Digital Innovation Lab, Aristotle University of Thessaloniki, described how ENoLL's Living Lab Revolution empowers global innovation and assists the co-design process of policies.  Established in 2006 under the EU presidency of Finland, ENoLL has evolved into a dynamic force fostering open innovation and co-creation across the globe. With a mission to promote the Living Lab concept, influence policies, and enhance Living Labs internationally, ENoLL has grown into a community with over 160 active members spanning 5 continents and 36 countries. At the heart of ENoLL's services is the Certification and Labelling program, where rigorous quality evaluations ensure high-value exchanges, quality outputs, and prevent the devalorization of Living Lab values. The organisation offers a Capacity Building program tailored for entities and professionals interested in creating or enhancing a Living Lab. ENoLL's thematic task forces and working groups facilitate knowledge exchange on hot topics such as rural Living Labs, energy and environment, social innovation, AI, and more. By emphasising open and user-driven innovation, Living Labs emerge as regional innovation hubs, building trustful environments for diverse stakeholders. ENoLL's unique role in policy Living Labs, co-designing new policies and applying Living Labs methodologies, sets it apart, contributing to iterative policy improvements. The certification process, harmonised procedures, and commitment to user-driven innovation make ENoLL Living Labs the global standard, embodying a culture of trust, collaboration, and excellence.

Last speaker, Mr. Creek, co-founder at Stickydot srl, showcased the Co-Creation in Action: The MOSAIC Case Study Unveiled. MOSAIC, a pioneering initiative focused on achieving climate-neutral cities, unfolded a groundbreaking co-creation methodology in Gothenburg and Milan. As a collaborative effort with EU funding and five partners, MOSAIC engaged in open innovation and quadruple-helix collaboration, bringing together stakeholders from government, industry, academia, and citizens. In Gothenburg, the project underwent three key phases, starting with challenge definition and stakeholder mapping, followed by stakeholder recruitment and a pivotal gathering event, and concluding with ideation, designing, and prototyping. The challenges centred around sustainable mobility in Gothenburg, with three distinct ideas emerging: a social car-pooling app, transforming a parking area into a sustainable community space, and introducing a mobility hub for families in the suburbs. The process revealed valuable lessons, emphasising the commitment to utilising co-creation outcomes, the complexity of stakeholder involvement, the need for careful assessment of conflicting interests, and the importance of professional facilitation and supportive conditions for citizens' engagement. MOSAIC demonstrated that co-creation when executed diligently, yields tangible and innovative solutions with real impact.