Stakeholders and Case Studies
Stakeholders
The TANGO framework's effectiveness and real-world utility are validated through deep engagement with a diverse group of stakeholders across four high-impact case studies. The consortium includes universities, research centers, NGOs and industry leaders, ensuring a holistic approach that connects research with practical application and societal needs. Key stakeholders include citizens, vulnerable populations represented by NGOs like SHARE and A11, and governmental bodies such as Serbia's Ministry of Family Welfare and Demography (MFWD).
Case Studies
The four case studies are:
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Supporting Women in Perinatal Health and Well-being: This study aims to empower women during pregnancy and postpartum with a personalized AI agent. In collaboration with the University Hospital Heidelberg (UKHD), the agent will engage in dialogues with approximately 500 women to monitor their health, understand their fears and needs and provide appropriate, understandable suggestions to improve outcomes for both mother and child. The stakeholders are expectant mothers, gynaecologists, neonatologists and healthcare providers.
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Supporting Surgical Teams in Intraoperative Decisions: In this technically complex scenario, an AI agent will assist surgical teams during the treatment of abdominal aortic aneurysms. Developed with partners like Azienda Provinciale per i Servizi Sanitari (APSS) and Surgical Science, the system will be tested in an augmented reality operating room to improve team coordination and help make critical decisions that minimize the risk of unfavorable outcomes. Stakeholders include surgeons, anaesthesiologists and medical training institutions.
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Fostering Fairness in Credit Lending: In partnership with Intesa San Paolo, Italy's largest bank, this case study addresses fairness and transparency in loan decisions. The TANGO system will support bank officers by complementing their expertise and flagging potential biases in historical data. For loan applicants who are denied, the system provides transparent explanations and offers interactive, actionable algorithmic recourse to help them improve their chances of approval.
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Shaping Fair Social Welfare Policies: This study supports policy makers in designing transparent and equitable social welfare policies. The system is a human-in-the-loop tool developed with the Government of Serbia and NGOs to help officials better understand vulnerable groups and the potential impact of different policies. By involving government actors, citizens and civil society, this case study aims to maximize societal welfare and ensure policies are created in a transparent and efficient manner.