EmpathiCH aims at bringing together and blend different expertise to develop new research agenda in the context of “Empathy-Centric Design at Scale”. The main research question is to investigate how new technologies can contribute to the elicitation of empathy across and within multiple stakeholders at scale; and how empathy can be used to design solutions to societal problems that are not only effective but also balanced, inclusive, and aware of their effect on society. Through presentations, participatory sessions, and a living experiment—where data about the peoples’ interactions is collected throughout the event—we aim to make this workshop the ideal venue to foster collaboration, build networks, and shape the future direction of “Empathy-Centric Design at Scale”.

Traditional approaches to data-informed policymaking are often tailored to specific contexts and lack strong citizen involvement and collaboration, which are required to design sustainable policies. We argue the importance of empathy-based methods in the policymaking domain given the successes in diverse settings, such as healthcare and education. In this paper, we introduce COCTEAU (Co-Creating The European Union), a novel framework built on the combination of empathy and gamification to create a tool aimed at strengthening interactions between citizens and policy-makers. We describe our design process and our concrete implementation, which has already undergone preliminary assessments with different stakeholders. Moreover, we briefly report pilot results from the assessment. Finally, we describe the structure and goals of our demonstration regarding the newfound formats and organizational aspects of academic conferences.

Artificial intelligence (AI) applications can profoundly affect society. Recently, there has been extensive interest in studying how scientists design AI systems for general tasks. However, it remains an open question asto whether the AI systems developed in this way can work as expected in different regional contexts while
simultaneously empowering local people. How can scientists co-create AI systems with local communitiesto address regional concerns? This article contributes new perspectives in this underexplored direction atthe intersection of data science, AI, citizen science, and human-computer interaction. Through case studies,
we discuss challenges in co-designing AI systems with local people, collecting and explaining communitydata using AI, and adapting AI systems to long-term social change. We also consolidate insights into bridgingAI research and citizen needs, including evaluating the social impact of AI, curating community datasets for
AI development, and building AI pipelines to explain data patterns to laypeople.