We are at a moment where the decisions being made about how to design, deploy, and govern AI will shape systems that society will depend on for decades. Those decisions are not primarily technical. They are decisions about how responsibility is distributed, how human judgment interacts with automated systems, how trust is built and lost in high-stakes environments, and what it means to design for resilience rather than just efficiency. They are decisions that require people who can think across disciplines, hold complexity without collapsing it prematurely, and ask hard questions even when the pressure is to move fast and deliver.

This challenge, developed in the context of ECIU University at Linköping University in Sweden, was built on the belief that engineers, business students, and social scientists need to learn to work on problems together, not alongside each other, but genuinely together,bringing different kinds of knowledge to bear on questions that none of them can answer alone. We found search and rescue to be a particularly good problem for that. It involves autonomous systems and sensor networks, but also organisational culture and volunteer motivation. It involves data infrastructure, but also legal accountability and public trust. It is technically complex and humanly complex in equal measure, and neither complexity can be understood without the other.

The students who took on this challenge did so with seriousness and curiosity. They were asked to engage with real difficulty, to resist the pull toward easy solutions, to question their own assumptions, and to think carefully about what it actually takes for AI to create value in systems that involve many actors, imperfect information, and consequences that matter. The work in this report is the result of that effort.

We are grateful to Jesper Tordenlid and WARA-PS for bringing a real problem to the course,an active research agenda with genuine open questions. That generosity made a difference to what the students were able to produce. We are grateful to Katarina Iversen for the scenario game that opened the course, which placed students inside the operational complexity of a rescue mission before they had the language to describe what they were experiencing. That ordering, feeling the problem before analysing it, shaped much of what came after. And we are grateful to Pascal Le Masson and Antoine Bordas from Mines Paris PSL for introducing students to design theory and the ideas around managing the unknown. Their contribution gave students not just a framework but a different way of thinking about what innovation in uncertain conditions actually demands.

The problems this challenge addresses are becoming more urgent as AI moves to autonomous agents. The students who worked through this challenge are among those who will have to navigate that transition, not just as users of AI, but as the people designing the systems, the organisations, and the governance structures that determine whether AI integration goes well or badly. That is a serious responsibility, and it requires exactly the kind of cross-disciplinary,critically grounded thinking this challenge was designed to develop.