Artificial intelligence (AI) and machine learning models are being increasingly deployed in
real-world applications. In many of these applications, there is strong motivation to develop …

While AI has benefited humans, it may also harm humans if not appropriately developed. We
conducted a literature review of current related work in developing AI systems from an HCI …

The main challenges are discussed together with the lessons learned from past and
ongoing research along the development cycle of machine learning systems. This will be …

We witnessed great advancement in artificial intelligence (AI) powered technologies over
the past few decades. Wide use of AI technologies has led to the creation of an ecosystem …

This study investigates the role of human intervention in artificial intelligence/machine
learning (AIML)-driven predictions. By doing so, we distinguish between three different types …

Any functional human-AI-robot team consists of multiple stakeholders, as well as one or
more artificial agents (eg, AI agents and embodied robotic agents). Each stakeholder's trust …

With the spreading of Industry 4.0, cyber-physical systems, and tools for augmented and
virtual reality, Digital Twin (DT) is gaining momentum in several areas of Computer Science …

An increasingly common use case for machine learning models is augmenting the abilities
of human decision makers. For classification tasks where neither the human nor model are …

Human-AI conversation provides a natural, unobtrusive, yet under-explored way to
investigate trust dynamics in human-AI teams (HATs). In this paper, we modeled dynamic …

In this prospective observational study, we investigate the role of transactive memory and
speaking up in human-AI teams comprising 180 intensive care (ICU) physicians and nurses …