The Influence of Interdependence on Trust Repair in Human-Agent Teams: Comparing the Effectiveness of Trust Repair Strategies in Full Independence and Complementary Independence

As autonomous systems are increasingly integrated as a team member for collaborative tasks, trust in human-agent teams (HAT) becomes crucial to foster success. In many real world scenarios, trust violations are expected, thus demanding the use of trust repair strategies to restore damaged trust. Previous research has shown that expressing regret...

The Influence of Interdependence Relationships on Trust Repair Strategies and Collaboration Fluency

Intelligent agents are increasingly required to engage in collaboration with humans in the context of human-agent teams (HATs) to achieve shared goals. Interdependence is a fundamental concept in teamwork. It enables humans and robots to leverage their capabilities and collaboratively work towards a shared goal, fostering the development of...

Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns

When humans and AI-agents collaborate, they need to continuously learn about each other and the task. We propose a Team Design Pattern that utilizes adaptivity in the behavior of human and agent team partners, causing new Collaboration Patterns to emerge. Human-AI Co-Learning takes place when partners can formalize recognized patterns of...

Assessing the Changes in Human Trustworthiness as a Result of an Artificial Agent Directing the Human in Joint Activities

The number of collaborations between humans and artificial agents has risen steeply in recent years due to the rapid expansion of AI. Numerous studies in social sciences have already established that trust is a crucial factor in ensuring effective teamwork. While the dynamics of trust in human-human relationships or the effects of human...

Tailoring User-Aware Agent Explanations to Properly Align Human Trust

Aligning human trust to correspond with an agent's trustworthiness is an essential collaborative element within Human-Agent Teaming (HAT). Misalignment of trust could cause sub-optimal usage of the agent. Trust can be influenced by providing explanations which clarify the agent's actions. However, research often approaches explanations...

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...

Assessing artificial trust in human-agent teams: A conceptual model

As intelligent agents are becoming human's teammates, not only do humans need to trust intelligent agents, but an intelligent agent should also be able to form artificial trust, i.e. a belief regarding human's trustworthiness. We see artificial trust as the beliefs of competence and willingness, and we study which internal factors (krypta) of...

Influence of shared information on predictability in human-agent teams

Understanding trust in human-agent teams is of utmost importance if we want to ensure an efficient and effective collaboration. It is well known that predictability is a core component of trust, however it is still unclear what kind of information an agent should share in order to be perceived as predictable. Here we show that in a simple world...

The Influence of Information Sharing on the Predictability of the Human to an Agent

Mutual predictability shows itself as a contributing factor to mutual trust and is known to improve the effectiveness in a human-agent teamwork setting. As team members communicate to coordinate the team through the task, the question arises as to what information the human should share to be predictable to an agent. To experiment with measuring...

Moral Decision Making in Human-Agent Teams: Human Control and the Role of Explanations

With the progress of Artificial Intelligence, intelligent agents are increasingly being deployed in tasks for which ethical guidelines and moral values apply. As artificial agents do not have a legal position, humans should be held accountable if actions do not comply, implying humans need to exercise control. This is often labeled as...

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...

Allocation of moral decision-making in human-agent teams: a pattern approach

Artificially intelligent agents will deal with more morally sensitive situations as the field of AI progresses. Research efforts are made to regulate, design and build Artificial Moral Agents (AMAs) capable of making moral decisions. This research is highly multidisciplinary with each their own jargon and vision, and so far it is unclear...