Workshop on Trust and Reliance in AI-Human Teams (TRAIT)

Abstract

As humans increasingly interact (and even collaborate) with AI systems during decision-making, creative exercises, and other tasks, appropriate trust and reliance are necessary to ensure proper usage and adoption of these systems. Specifically, people should understand when to trust or rely on an algorithm's outputs and when to override them. Significant research focus has aimed to define and measure trust in human-AI interaction, and design and implement interactions that promote and calibrate trust. However, conceptualizing trust and reliance, and identifying the best ways to measure these constructs and effectively shape them in human-AI interactions remains a challenge, especially across contexts and domains. This workshop aims to establish building appropriate trust and reliance on (imperfect) AI systems as a vital, yet under-explored research problem. The workshop will provide a venue for exploring three broad aspects related to human-AI trust: (1) How do we clarify definitions and frameworks relevant to human-AI trust and reliance (e.g., what does trust mean in different contexts)? (2) How do we measure trust and reliance? And, (3) How do we shape trust and reliance? The workshop will build on the success from running it at CHI 2022,1 with a focus on "Learning from Practice"- how can we better tie theory-building to real-life use cases? As these problems and solutions involving humans and AI are interdisciplinary in nature, we invite participants with expertise in HCI, AI, ML, psychology, and social science, or other relevant fields to foster closer communications and collaboration between multiple communities.