AI for Collective Goals and a Better World

Artificial intelligence (AI) has become pervasive and present in every aspect of our life. It is a revolutionary technology that with massive data, computing power, machine learning and human inputs can do more than what humans can do. Humans are a crucial part of AI development in two fundamental ways: by providing instructions and feedback learning when using AI, and by choosing the goals of AI itself. What do we know about which type of AI can be built AI and the goals of these systems?

Mission: To promote knowledge and understanding of what AI is and start an active debate on which type of AI we want and need to develop. The transformative power of AI can be used for the benefits of all only with full transparency on who constructs AI, how and for which collective goals.

Why Artificial Intelligence - YAI?

What we do

• Wepromote and develop purpose-specific AI: AI tools that help solve problems that humans cannot solve.

• The problem-focused AI with a specific purpose will not be an AI we have to adapt to, but rather an AI that helps advancing society.

• Compared to general-purpose LLMs Models, this problem-focused AI will be greener and privacy-respectful by using much less energy and being trained on dedicatedly curated datasets rather than on massive data scraped from the web.

Goals

• Promote a vision and create a community that shape the priorities, set the agenda and lead the development of AI for society.

• Support research projects that transparently build AI with clear collective goals and explicitly account for the differential impact of AI on different groups.

• Organize and promote dissemination activities on building AI for society.

Target Audience

• Researchers developing and applying AI and machine learning in social contexts.

• Practitioners using AI for policy analysis, decision-making, and socially oriented applications.

• Researchers and professionals engaged in responsible AI, and in the ethical, methodological, and societal implications of data-driven systems.

• Civil society organizations and non-profit organizations that develop and promote training courses and educational programs on AI.

Team

Dr Chiara Binelli, YAI Program Director

Dr Matthew Loveless, YAI Senior Researcher

Tess Meggiolaro, YAI Junior Researcher

Women Shaping the Future of AI for Society

Women have made significant contributions to the development of machine learning and AI for society, but their voices and influence are underrepresented. We insist on a world where female voices exercise real authority over which type of AI is built, whose societal needs it addresses, and how it is used in society

Mission: to make the female voice on AI for society heard. We connect women working on AI for society in Data Science and Social Science, and develop natural pathways from mentorship to collaboration to impact.

What we do

Mapping Women’s Contributions to Artificial Intelligence Using Large-Scale Text Analysis

We are developing the first computational mapping of women’s contributions to AI research in Social Science and Data Science. Using all papers published in Social Science and Data Science on arXiv and socarxiv between 2023 and 2026, we find that female-led AI research differs significantly from male-led AI research in two key aspects:

• It covers more diverse topics than male-led studies and the field average.

• Women prominently focus on issues of wide significance, such as AI’s policy implications, explainability, and AI’s consequences and impacts, not just its mechanisms.

Why does it matter? Participation in AI research shapes which type of AI is built, whose societal needs it addresses, and how it is used in society. The female voice on AI in research differs significantly from the field's average. Women should sit at the decision-making tables and shape the societal impacts of AI.

Goals

• Facilitate joint ventures among women working at the intersection of AI and society.

• Organize and promote dissemination activities on building inclusive AI for society.

• Provide resources for mentorship and career development from students to professionals.

• Be a strong, representative force that shapes priorities, sets the agenda, and leads the societal impact of AI.

Target Audience

WINDS targets a set of audiences working at the intersection of data science and social science. Its primary target audiences include:

• Researchers applying AI and machine learning in social contexts.

• Students seeking training, mentorship, and career pathways in data-intensive social science.

• Practitioners using data science for policy analysis, decision-making, and socially oriented applications.

• Researchers and professionals engaged in responsible AI, and in the ethical, methodological, and societal implications of data-driven systems.

Team

Dr Chiara Binelli, WINDS Program Director
Dr Elena Cossu, WINDS researcher

Predict to Explain

A fundamental divide persists between Social Science, which prioritizes explanation and causal understanding, and Data Science, which emphasizes prediction and forecasting. Separately, each approach is limited. However, what if the strengths of the explanatory and predictive approaches could be combined?

Mission: Predict to Explain seesk to develop a framework that combines the explanatory strengths of Social Science with the predictive capabilities of Data Science. This improves how evidence is generated and evaluated, in turn used to improved theory development and explaining future outcomes. In this way, Predict to Explain strengthens both scientific insight and real-world decision-making.

What we do

• Combining prediction with explanation can be used to develop better theories of human behavior and one of the primary goals of Social Science research, the very ability to explain reality.

• We propose a framework that embeds prediction into research design and empirical analysis to increase explanatory power and strengthen theory robustness.

Goals

• Identify and bridge the complementary research approaches of Social Science and Data Science.

• Evaluate and expand the scientific, explanatory quality of Social Science research.

• Develop and promote a combined framework for theory-development: Predict to Explain

• Explore the approach in the study of key questions in Social Science.

• Update core methodological thinking and implementation in the social sciences.

Target Audience

• Applied Social Science and Data Science researchers.

• Social Science and Data Science students.

• Researchers and professional practitioners in the fields of policy analysis, forecasting, decision-making, and socially oriented applications.

Team

Dr Chiara Binelli, PTE Program Director

Dr Matthew Loveless, PTE Senior Researcher

Amélie Benková, PTE Junior Researcher

Democracy in the Future

We are in poly-crisis. Elections, economic performance, public health, and geopolitical stability have all become increasingly unpredictable. Democracies and their citizens are operating under conditions of widening uncertainty. In the social sciences, research has struggled to incorporate citizens’ expectations – and uncertainty – about the future into models of political attitudes and behavior. How do citizens expect the future to unfold – economically, politically, and institutionally? And how does that shapes their evaluations of governments, political participation, and support democratic systems in the present?

Mission: To develop and apply a rigorous framework for measuring citizens’ subjective expectations about future political and economic outcomes, and to integrate these expectations into models of democratic system support at the national and European levels.

What we do

• A more realistic and forward-looking understanding of democratic politics - one that treats citizens not as unidimensional evaluators of past performance but who can, and do, continuously anticipate, assess, and respond to uncertain futures.

• By systematically incorporating expectations and uncertainty into political analysis, Democracy in the Future program aims to improve both democratic theory and empirical models of political behavior.

Goals

• To overcome existing limitations in behavioral research to include and reliably assess individuals’ future expectations

• To establish individual expectations and uncertainty as core components of political behavior models by advancing methodological standards for measuring subjective beliefs.

• To merge novel data collection methodologies such as machine learning and the Quantitative Expectations Data (QED) survey methodology to better elicit individuals’ subjective probability distributions over future outcomes.

• To improve theory development by linking uncertainty to political attitudes, Support for national governments and democratic institutions, evaluations of democratic performance and legitimacy, and political participation, including voting and engagement

Target Audience

• Social science, behavioral researchers in and adjacent to academia.

• To aid policy-makers abilities to anticipate public reactions to future-oriented reforms and identifies conditions under which uncertainty undermines or stabilizes system support.

Team

Dr Matthew Loveless, Democracy in the Future Program Director

Europe-Asia Programme

Bridging Europe & Asia for a Stable Global Order

Europe-Asia relations are pivotal in shaping global politics, economics, and security amidst rising geopolitical tensions, trade frictions, and technological shifts. Balanced, forward-looking dialogue between European and Asian stakeholders remains underrepresented. CERSP insists on fostering robust platforms where diverse voices from Europe and Asia drive collaborative policy solutions for a multipolar world. Understanding this evolving partnership is crucial for interpreting how both regions navigate economic interdependence, strategic autonomy, and global governance challenges in the twenty-first century.

Mission: Position the Europe-Asia Programme at CERSP as a leading hub for advancing pragmatic, evidence-based cooperation between Europe and Asia through strategic exchanges among policymakers, researchers, and practitioners

What we do

• Strategic Europe-Asia partnerships seeks to address the world's most pressing challenges, from trade imbalances and supply chain resilience to geopolitical stability and sustainable development.

• The Europe-Asia Programme facilitates connections among experts in international relations, political economy, and policy analysis to build pathways from dialogue to joint initiatives and tangible impact.

Goals

• Facilitate joint research ventures and policy projects bridging Europe and Asia on key issues such as EU-China Relations, Belt and Road Initiative (BRI) impacts, and regional security.

• Organize and promote dissemination activities, including conferences, workshops, and publications on inclusive, mutually beneficial Europe-Asia frameworks.

• Serve as a strong, representative force that shapes policy priorities, sets the agenda for think tank discourse, and leads societal and geopolitical impact in Europe-Asia relations.​

Target Audience

Stakeholders at the nexus of International Relations, Global Political Economy, and policy practice. Primary audiences include:

• Researchers applying comparative analysis to Europe-Asia dynamics, including EU- China Relations and the rise of Global Populism.

• Students seeking training, mentorship, and pathways in Europe-Asia focused Political Science and Policy Studies.

• Practitioners using policy analysis for decision-making in diplomacy, trade negotiations, and think tank advisory roles.

• Experts engaged in geopolitical foresight, economic strategy, and the strategic implications of Europe-Asia interconnections.

Team

Dr. James F. Downes, Europe-Asia Program Director

Populism

What we do

• CeRSP envisions a Europe that can reconcile openness with coherence, strengthening democratic institutions while responding effectively to societal concerns about immigration and identity politics.

• Bridging academic research and policy debate, the programme aims to illuminate pathways toward civic inclusion, social trust, and adaptive governance in the age of populism.

Goals

• Advance comparative research on far-right populism, immigration, and governance across EU member states and in comparative perspective with other regions.

• Foster multidisciplinary exchanges amongst scholars, policymakers, and civil society/non-governmental organizations on the causes, consequences, and counterstrategies for populist movements.

• Provide an evidence base for policy innovation in immigration management, liberal democratic participation, and institutional reform.

• Contribute to a global understanding of populism’s interaction with political economy, digital communication, and identity politics.

Target Audience

• Policymakers and think tank analysts seeking evidence-based insights for designing inclusive and resilient governance systems.

• Researchers studying European politics, populism, comparative governance, and immigration.

• Civil society actors and educators promoting liberal democratic engagement and intercultural dialogue.

• Journalists and public communicators interested in interpretive and data-driven analysis of populist trends.

Team

Dr. James F. Downes, Populism Program Director