TWIN4DEM brings together scholars of the social sciences and humanities, computational social sciences (CSS) and democracy stakeholders to jointly address one of the most pressing contemporary issues: what causes democracies to backslide? Combining various advanced CSS methods, TWIN4DEM prototypes the first ever digital twins of four European democratic systems (Czechia, France, Hungary and the Netherlands). In doing so, TWIN4DEM delivers four major breakthroughs. First TWIN4DEM develops a new agent-based conceptual model allowing to identify the causal pathways leading to executive aggrandisementn - the excessive concentration of powers into national executives - and threatening rule-of-law institutions. This will allow the systematic identification and testing of new hypotheses on the multidimensional causes of democratic backslide. Second, TWIN4DEM releases new cross-cutting tools to process and aggregate textual and non-textual data more efficiently and in real-time in an open, FAIR and GDPR-compliant manner. TWIN4DEM tools will not only allow democracy researchers to process more effectively the abundance of data on political life but also to enhance the transparency and legitimacy of democratic decision-making. Third, TWIN4DEM simulates, together with national policy makers and civil society organizations, policy scenarios to prevent and react against democratic backslide. This will enhance the effectiveness of interventions aiming at shielding rule-of-law institutions against external and internal threats. As a result, European democracies will be more resilient. Fourth, by formulating guidelines on scaling up the use of CSS in democracy research in a participatory, open and ethics-driven manner, TWIN4DEM paves the way for using such methods in a way that empowers citizens and reinvigorates the quality of democratic governance.

FINDHR is an interdisciplinary project that seeks to prevent, detect, and mitigate discrimination in AI. Our research will be contextualized within the technical, legal, and ethical problems of algorithmic hiring and the domain of human resources, but will also show how to manage discrimination risks in a broad class of applications involving human recommendation. Through a context-sensitive, interdisciplinary approach, we will develop new technologies to measure discrimination risks, to create fairness-aware rankings and interventions, and to provide multi-stakeholder actionable interpretability. We will produce new technical guidance to perform impact assessment and algorithmic auditing, a protocol for equality monitoring, and a guide for fairness-aware AI software development. We will also design and deliver specialized skills training for developers and auditors of AI systems. We ground our project in EU regulation and policy. As tackling discrimination risks in AI requires processing sensitive data, we will perform a targeted legal analysis of tensions between data protection regulation (including the GDPR) and anti-discrimination regulation in Europe. We will engage with underrepresented groups through multiple mechanisms including consultation with experts and participatory action research. In our research, technology, law, and ethics are interwoven. The consortium includes leaders in algorithmic fairness and explainability research (UPF, UVA, UNIPI, MPI-SP), pioneers in the auditing of digital services (AW, ETICAS), and two industry partners that are leaders in their respective markets (ADE, RAND), complemented by experts in technology regulation (RU) and cross-cultural digital ethics (EUR), as well as worker representatives (ETUC) and two NGOs dedicated to fighting discrimination against women (WIDE+) and vulnerable populations (PRAK). All outputs will be released as open access publications, open source software, open datasets, and open courseware.

SHIFT is strategically conceived to deliver a set of loosely coupled, technological tools, that offers cultural heritage institutions the necessary impetus to stimulate growth, and embrace the latest innovations in artificial intelligence, machine learning, multi-modal data processing, digital content transformation methodologies, semantic representation, linguistic analysis of historical records, and the use of haptics interfaces to effectively and efficiently communicate new experiences to all citizens (including people with disabilities). The development of SHIFT tools will be carried out in close consultation with the stakeholder communities represented in the project. The two CH networks (BMN, ANBPR) will launch open consultation to aggregate views from their members, while together with the cultural heritage institutions (SOMKL, SMB) and heritage professionals (Heritage Management), will provide requirements based on the cultural assets being maintained within each organisation. The diversity of digital media transformation and the semantic formalisation of the cultural assets will be individually demonstrated across each museum and library. Additionally, the inclusion by design principles adopted within the project, will be evaluated by CH networks and vulnerable group partner (DBSV), who will engage with the various tools developed in the project. In complementary to the stakeholders and end-users, the SHIFT project also brings together leading industrial (SIMAVI) and academic institutions (FORTH, UAU, QMUL). The consortium is complemented by SMEs (MDS, AUD) with high-tech product development teams and ethical expertise (ERC). Collectively, the project will release 12 technology solutions clustered into five thematic areas (computer vision, audio, text-to-speech, haptics, semantics and linguistics) that support accessibility and inclusion by design to overcome the shortcomings and limitations of CCI sector to enable growth and stimulation.

MADRAS project aims to demonstrate a materials-driven improvement of OLAE devices, establishing a high speed manufacturing methodology in a scalable competitive process which is In Mold Hybrid Printed Electronics (IMHyPE). Four high performance materials to be developed in MADRAS tackle high cost, instability and short lifetime of OLAE devices under operational conditions through the development of robust alternatives and innovative approaches. Such materials are a conductive and transparent substrate, a semiconducting transparent ink based on organic components, a transparent conductive silver nanowire-based ink and a semiconductor ink based on metal oxide nanoparticles. MADRAS project also addresses the need for innovative and industrial manufacturing processes for the development of robust series of flexible plastronic products. Building on an already established technology as plastic injection, will facilitate a faster uptaking. The advantages of IMHyPE are numerous and include: light weighting, space-saving, robustness, accelerated time-to-market, and high throughput capabilities. It will demonstrate processability, stability, operational lifetime and seamless integration of new products as well as of new technology into traditional goods. Therefore, MADRAS proposes two products for persons’ authentication market and smart manufacturing that will show a step forward towards digitisation and Internet of Things for its contribution to the sustainable deployment of smart products for consumer use. Ethical issues for these matters are properly addressed. Such products belong to the global emerging trend of structural electronics with very large addressable markets as Automotive sector, healthcare and many others. The workplan sets and consolidates the value chain through the participation of six SMEs, four RTOs, one large company and one standardisation association completing MADRAS consortium assuring high impact boosting activities.