AIOLIA gives a robust 3-tier response to the complex challenges posed by the need to operationally interpret the EU AI Act and global AI regulation. (1) Recognizing the gap between ethical values and their practical application in engineering, AIOLIA pioneers a bottom-up approach to operationalize AI ethics with regard to human condition and behaviour. Following a selection of real-world use cases, AIOLIA translates high-level principles into actionable and contextual guidelines co-created by leading academic, policy, and ethics-aware industrial partners who represent diverse professional and geographic European and international contexts. (2) AIOLIA's commitment to context-sensitivity is deepened by crafting modular, inclusive training materials following the ADDIE methodology designed to cater to diverse learning needs. Hosted on the Embassy of Good Science, AIOLIA materials will range from lectures, videos, and mock reviews to such innovative formats as podcasts, Tiktoks, and a chatbot teaching AI ethics. (3) AIOLIA's outreach is amplified by encompassing 7 research ethics and integrity networks and 3 prominent computer science networks. This strategic alignment enables us to effectively recruit training participants and disseminate human-centric ethics guidelines to a wide spectrum of stakeholders, from ethics experts to early-stage researchers and policymakers worldwide. Resolutely European, AIOLIA's vision propagates beyond EU, embracing global cooperation with leading universities and think tanks in China, South Korea, Japan, and Canada. Utilizing UNESCO platform with its reach to Africa and South Asia, AIOLIA’s guidelines evolve into an analytic toolbox for key international AI dialogues and processes. This global perspective ensures that AIOLIA's impact is not only significant but also sustainable, contributing to fair scientific cooperation and providing concrete and culturally informed ethics instruments to shape the next generation of AI systems.

Whilst citizen participation in environmental policy making is still in its infancy, there are signs of a growing level of interest. The majority of citizens, though, both as individuals and as groups often feel disengaged from influencing environmental policies. They also remain unaware of publicly available information, such as the GEOSS or Copernicus initiatives. The SCENT project will alleviate this barrier. It will enable citizens to become the ‘eyes’ of the policy makers by monitoring land-cover/use changes in their everyday activities. This is done through a constellation of smart collaborative technologies delivered by the SCENT toolbox in TRLs 6-8: i) low-cost and portable data collection tools, ii) an innovative crowd-sourcing platform, iii) serious gaming applications for a large-scale image collection and semantic annotation, iv) a powerful machine-learning based intelligence engine for image and text classification, v) an authoring tool for an easy customization by policy makers, vi) numerical models for mapping land-cover changes to quantifiable impact on flood risks and vii) a harmonization platform, consolidating data and adding it to GEOSS and national repositories as OGC-based observations. SCENT will be evaluated in two large scale demonstrations in Kifisos Attica and Danube Delta. Our consortium covers the complete stakeholder chain: industries in machine learning (IBM), SMEs in crowd-sourcing (U-Hopper), gaming (Xteam) and awareness raising (Carr), leading research institutes with expertise in hydrodynamic modelling (UNESCO-IHE), data harmonization and authoring tools (ICCS) and environmental monitoring (DDNI), NGOs at the pilot sites (HRTA, SOR) and policy makers/public bodies (Region of Attica). The SCENT initiative will go beyond the current project and form a European-wide citizen movement, created and fostered by the SCENT stakeholders, that will ensure its sustainability and its complementarity with existing citizen partnerships.

Diversity permeates our everyday life and covers many dimensions, such as competence, culture, gender or economic across humans and social relations. Technology has evolved to a point where humans from diverse backgrounds, cultures, and experiences have an unprecedented ability to connect with each other. Yet technology does not in-and-by-itself provide support for developing and maintaining the social relationships that transcend geographical and cultural backgrounds. WeNet addresses this gap by providing a diversity-aware, machine-mediated paradigm of social relations. The goal is connecting people that can support each other, and the key is leveraging their diversity. The WeNet paradigm includes a family of computational diversity-aware models supporting human interaction. Learning models construct diversity profiles based on people's past behaviour and interactions. A diversity-aware search builds upon these profiles to connect the "right" people together. To support people’s interactions, a diversity alignment mechanism lifts communication barriers to ensure that messages between humans are interpreted correctly, and a diversity-aware incentive mechanism generates incentives to motivate people to support each other. The entire paradigm is developed taking into consideration ethical guidelines. The WeNet platform provides the technological infrastructure to set out a series of studies that will be carried within universities worldwide with diverse student populations, and with the final goal of improving students' quality of life inside and outside the academic environment. Beyond universities, WeNet's innovative paradigm impacts human interactions in general, especially those that may benefit from a collaborative approach (creative industries, medical diagnosis, ...). The WeNet consortium will develop a research infrastructure that will allow the exploitation of the project results and strengthen the European innovation eco-system in a worldwide perspective.

Artificial Intelligence (AI) holds enormous potential for enhancing human decisions, improving cognitive overload and lowering bias in high-stakes scenarios. Adoption of AI-based support systems in such applications is however minimal, chiefly due to the difficulty of assessing their assumptions, limitations and intentions. In order to realise the promise of AI for individuals, society and economy, people should feel they can trust AIs in terms of reliability, capacity to understand the human’s needs, and guarantees that they are genuinely aiming at helping them. TANGO will develop the theoretical basis and computational framework for hybrid decision support systems (HDSS) in which humans and machines are aligned in terms of values and goals, know their respective strengths, and work together to reach an optimal decision. To this end, TANGO will develop: 1) A cognitive theory of mutual understanding and hybrid decision making, of intuitive vs deliberative approaches to decision making and of how they affect our trust in human and AI teammates. 2) Cognition-aware explainable AIs implementing synergistic human-machine interaction, enabling machines to determine what information a specific decision maker (e.g., layperson vs expert) needs, or does not need, to reach an informed decision. 3) A “Human-in-the-loop” co-evolution of human decision making and machine learning models building on bi-directional, explanation-augmented interlocution. The TANGO framework will be evaluated on four high impact use cases, namely supporting: i) women during pregnancy and postpartum, ii) surgical teams in intraoperative decision making, iii) loan officers and applicants in credit lending decision processes, and iv) public policy makers in designing incentives and allocating funds. Success in these case studies will establish TANGO as the framework of reference for developing a new generation of synergistic AI systems, and will strengthen the leadership of Europe in human-centric AI.