The immigration debate is a major source of political conflict, yet little is known about how citizens themselves perceive it. This paper uses a survey experiment with open-ended questions to examine which arguments respondents attribute to their opponents, which they consider the strongest for the opposing side, and how both compare to the arguments opponents actually use. The study is conducted in Norway, a low-polarization, consensus-oriented context where relatively accurate and charitable interpretations of opponents’ reasoning might be expected. Still, the findings show that while many recognize legitimate arguments on the other side, they attribute considerably weaker arguments to their opponents. Text analysis reveals that their preferred counterarguments resemble opponents’ own more closely than those they attribute to them. This suggests that mutual understanding in the immigration debate is obstructed less by a failure to appreciate opponents’ arguments than a systematic misrepresentation of them.

The robots of tomorrow should be endowed with the ability to adapt to drastic and unpredicted changes in their environment and interactions with humans. Such adaptations, however, cannot be boundless: the robot must stay trustworthy. So, the adaptations should not be just a recovery into a degraded functionality. Instead, they must be true adaptations: the robot must change its behaviour while maintaining or even increasing its expected performance and staying at least as safe and robust as before. The RoboSAPIENS project will focus on autonomous robotic software adaptations and will lay the foundations for ensuring that they are carried out in an intrinsically trustworthy, safe and efficient manner, thereby reconciling open-ended self-adaptation with safety by design. RoboSAPIENS will transform these foundations into ‘first time right’-design tools and platforms and will validate and demonstrate them.