Meaningful human control and variable autonomy in human-robot teams for firefighting

Introduction: Humans and robots are increasingly collaborating on complex tasks such as firefighting. As robots are becoming more autonomous, collaboration in human-robot teams should be combined with meaningful human control. Variable autonomy approaches can ensure meaningful human control over robots by satisfying accountability,...

Appropriate context-dependent artificial trust in human-machine teamwork

As human-machine teams become a more common scenario, we need to ensure mutual trust between humans and machines. More important than having trust, we need all teammates to trust each other appropriately. This means that they should not overtrust or undertrust each other, avoiding risks and inefficiencies, respectively. We usually think of...

Personalized Agent Explanations for Human-Agent Teamwork: Adapting Explanations to User Trust, Workload, and Performance

For human-agent teams to be successful, agent explanations are crucial. These explanations should ideally be personalized by adapting them to intended human users. So far, little work has been conducted on personalized agent explanations during human-agent teamwork. Therefore, an online experiment (n = 60) was conducted to compare personalized...

The influence of interdependence and a transparent or explainable communication style on human-robot teamwork

Humans and robots are increasingly working together in human-robot teams. Teamwork requires communication, especially when interdependence between team members is high. In previous work, we identified a conceptual difference between sharing what you are doing (i.e., being transparent) and why you are doing it (i.e., being explainable). Although...

A Two-Dimensional Explanation Framework to Classify AI as Incomprehensible, Interpretable, or Understandable

Because of recent and rapid developments in Artificial Intelligence (AI), humans and AI-systems increasingly work together in human-agent teams. However, in order to effectively leverage the capabilities of both, AI-systems need to be understandable to their human teammates. The branch of eXplainable AI (XAI) aspires to make AI-systems more...