People who design, use, and are affected by autonomous artificially intelligent agents want
to be able to trust such agents—that is, to know that these agents will perform correctly, to …

The spread of AI-embedded systems involved in human decision making makes studying
human trust in these systems critical. However, empirically investigating trust is challenging …

The wide adoption of Machine Learning (ML) technologies has created a growing demand
for people who can train ML models. Some advocated the term" machine teacher''to refer to …

Recent news coverage on pricing portrays the importance of price fairness. This article
conceptually integrates the theoretical foundations of fairness perceptions and summarizes …

Trust in a Recommender System (RS) is crucial for its overall success. However, it remains
underexplored whether users trust personal recommendation sources (ie other humans) …

This article presents a model of relational leadership based on a review of leader-member
exchange (LMX) and interpersonal trust. This model asserts that the LMX relationship is built …

Examining the ways in which affect impacts the trust that develops between members of
dissimilar groups broadens the study of trust development. People's perceptions of their own …

Positive public perceptions are a critical pillar of the criminal justice system, but the literature
addressing them often fails to offer clear advice regarding the important constructs or the …

Trusted AI literature to date has focused on the trust needs of users who knowingly interact
with discrete AIs. Conspicuously absent from the literature is a rigorous treatment of public …

The paper empirically examines the effects of social capital of the relationship between the
chief information officer (CIO) and top management team (TMT) on organizational value …