THESIS
2020
Abstract
Despite the growing role of Artificial Intelligence (AI) in organizational decision making, we do
not have consistent understanding on how employees would react to algorithmic decisions,
especially on the issues related to human resource (HR) management. In the current research, we
examine how outcome favorability affects people’s perception of AI agents and humans in terms
of fairness, sociability, and morality, and how these perceptions affect people’s response to
decisions made by the two entities. Findings from two experimental studies were as following: 1)
when the decision outcome is unfavorable, AI system is perceived fairer than human, and people
consequently respond more positively towards algorithmic decision than human decision, and 2)
when the decision outcome is fav...[
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Despite the growing role of Artificial Intelligence (AI) in organizational decision making, we do
not have consistent understanding on how employees would react to algorithmic decisions,
especially on the issues related to human resource (HR) management. In the current research, we
examine how outcome favorability affects people’s perception of AI agents and humans in terms
of fairness, sociability, and morality, and how these perceptions affect people’s response to
decisions made by the two entities. Findings from two experimental studies were as following: 1)
when the decision outcome is unfavorable, AI system is perceived fairer than human, and people
consequently respond more positively towards algorithmic decision than human decision, and 2)
when the decision outcome is favorable, human is perceived more sociable than AI system, and
people thus react more positively to human decision than algorithmic decision in general.
Theoretical and practical implication of the findings are discussed.
Keywords: Artificial intelligence, decision making, fairness, sociability, outcome acceptability,
employee engagement
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