Exploring the effect of the information amount in explanation on different gaming expertise levels

Explainable AI (XAI) has gained increasing attention from more and more researchers with an aim to improve human interaction with AI systems. In the context of human-agent teamwork (HAT), providing explainability to the agent helps to increase shared team knowledge and belief, therefore improving overall teamwork. With various backgrounds and...

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...

Agent Failure and Trust Repair in Human-Agent Teams: Interdependence Impact on Trust Repair Strategy and Collaboration Fluency in Human-AI Team

Interdependence relationships between humans and agents play a crucial role in the collaborative AI field. This research paper examines the impact of interdependence on trust violation, trust repair strategies, and collaboration fluency in human-AI teams. It compares independent cooperation and required interdependence approaches, focusing on...

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...

Agent Failure, Trust Repair, and Fluency in Human-AI Teams: Impact of Opportunistic Interdependence Relationship on Trust Violation, Trust Repair, and on Collaboration Fluency in a Human-Agent Team

Nowadays, Human Autonomy Teams (HATs) are incorporated in many fields, where humans and autonomous agents work collaboratively to combine their capabilities with the ultimate goal of performing tasks more efficiently. In such environments, it is imperative to sustain a high level of trust between the agents as collaboration is not possible...

The Influence of Adapting an Agent’s Explanation Style to a Human Team Leader Role on Human-Agent Teamwork during a Simulated Search and Rescue Task

Communication is one of the main challenges in Human-Agent Teams (HATs). An important aspect of communication in HATs is the use of explanation styles. This thesis examines the influence of an explainable agent adapting its explanation style to a supervising human team leader on team performance, trust, situation awareness, collaborative fluency...

Using Human Workload to Adjust Agent Explanations in Human-agent Teamwork

Artificial intelligence systems assist humans in more and more cases. However, such systems' lack of explainability could lead to a bad performance of the teamwork, as humans might not cooperate with or trust systems with black-box algorithms opaque to them. This research attempts to improve the explainability of artificial intelligence systems...

The Impact of Tailoring Agent Explanations According to Human Performance on Human-AI Teamwork

Nowadays, artificial intelligence (AI) systems are embedded in many aspects of our lives more than ever before. Autonomous AI systems (agents) are aiding people in mundane daily tasks, even outperforming humans in several cases. However, agents still depend on humans in unexpected circumstances. Thus, the main goal of these agents has...

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...

Sharing human mental model with an AI agent to achieve team effectiveness

The collaboration between AI agents (Artificial Intelligence) and human is an essential part of achieving complex goals more efficiently. Many aspects are influential in achieving effective teamwork. One of them is trust. In addition, sharing the mental model would improve the understanding of the other’s behavior and the prediction of their...

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...