Crowdsourcing moral machines - Jean-François Bonnefon
Machines increasingly make decisions or give advice that can substantially impact the life outcomes of humans. These decisions fall in the moral domain, especially when they involve tradeoffs between the life outcomes of different (group of) humans. Expert opinion (ethical and technical) is required for policymakers to solve these tradeoffs, but trust in machines will suffer if citizens are not given a voice in this debate. Here I'll describe how social scientists can build platforms that help crowdsourcing the moral values we want machines to display, using the examples of self-driving cars and the "moral machine experiment".
Cognitive Automation and Human-Autonomy Teaming in Manned unmanned Teaming Missions - Prof. Alex Schulte
This contribution will provide an overview of our research activities in Human-Autonomy Teaming (HAT) design patterns for military manned-unmanned teaming (MUM-T) missions. Therefore, we look into mission management and cockpit pilot assistance systems as well as multi-UAV teaming and swarming technologies. There will also be a strong focus on adaptive automation utilizing human mental state determination techniques and cognitive architectures. The contribution will also provide insight in our cognitive engineering approach to structure, describe and depict configurations for highly automated human-machine systems using a common language. Finally, this contribution will showcase application examples for highly automated HAT design patterns, implemented prototypes and validation experiments.