Artificial intelligence (AI) has the potential to improve human decision-making by providing
decision recommendations and problem-relevant information to assist human decision …

With the growing role of artificial intelligence (AI) in our lives, attention is increasingly turning
to the way that humans and AI work together. A key aspect of human–AI collaboration is how …

In sampling approaches to advice taking, participants can sequentially sample multiple
pieces of advice before making a final judgment. To contribute to the understanding of active …

Research on advice taking has demonstrated a phenomenon of egocentric discounting:
people weight their own estimates more than advice from others. However, this research is …

Algorithm-based decision support systems play an increasingly important role in decisions
involving exploration tasks, such as product searches, portfolio choices, and human …

Collaboration with other agents requires people to reflect on several aspects of their
collaborator's capabilities: How good are they at a task? Do they have access to the same …

Despite computational algorithms outperforming humans in certain tasks, algorithmic advice
is less used than human advice (algorithm aversion). Thus, algorithmic advice should be …

1.1. INTRODUCTION 10 willing to follow the advice depends heavily on the algorithm's
exploration tendency. Participants are more likely to follow an algorithm that is more …

Research on advice taking frequently utilizes a Judge Advisor System paradigm, in which a
judge reports a prior belief, receives advice, and then revises their initial estimate. However …

Advice-taking plays a critical role in collaboration. Yet people tend to under-utilize advice,
often to their own detriment. In this chapter, we investigate if people's utilization of advice …