How should an AI trust its human teammates? Exploring possible cues of artificial trust

In teams composed of humans, we use trust in others to make decisions, such as what to do next, who to help and who to ask for help. When a team member is artificial, they should also be able to assess whether a human teammate is trustworthy for a certain task. We see trustworthiness as the combination of (1) whether someone will do a task and ...

Integrity-based Explanations for Fostering Appropriate Trust in AI Agents

Appropriate trust is an important component of the interaction between people and AI systems, in that ‘inappropriate’ trust can cause disuse, misuse or abuse of AI. To foster appropriate trust in AI, we need to understand how AI systems can elicit appropriate levels of trust from their users. Out of the aspects that influence trust, this paper...

Exploring the effect of automation failure on the human’s trustworthiness in human-agent teamwork

Introduction: Collaboration in teams composed of both humans and automation has an interdependent nature, which demands calibrated trust among all the team members. For building suitable autonomous teammates, we need to study how trust and trustworthiness function in such teams. In particular, automation occasionally fails to do its job, which...

Artificial Trust for Decision-Making in Human-AI Teamwork: Steps and Challenges

Human-AI teams count on both humans and artificial agents to work together collaboratively. In human-human teams, we use trust to make decisions. Similarly, our work explores how an AI can use trust (in human teammates) to make decisions while ensuring the team’s goal and mitigating risks for the humans involved. We present the several steps...

Misalignment in Semantic User Model Elicitation via Conversational Agents: A Case Study in Navigation Support for Visually Impaired People

Disabled people can benefit greatly from assistive digital technologies. However, this increased human-machine symbiosis makes it important that systems are personalized and transparent to users. Existing work often uses data-oriented approaches. However, these approaches lack transparency and make it hard to influence the system’s behavior. In...