Location

Online

Event Website

https://hicss.hawaii.edu/

Start Date

4-1-2021 12:00 AM

End Date

9-1-2021 12:00 AM

Description

Artificial Intelligence (AI) and machine learning (ML) algorithms are changing the work in many ways. One hitherto little-studied area is how these technologies are impacting leader-employee relationships, particularly employees’ trust relationships in their “flesh-and-blood” leaders. In this paper, we discuss how algorithms change the nature of leadership when some leadership functions become automated. As a consequence, employees will often find themselves in a “two-leader-situation” with resulting frictions, that create novel leadership focus areas. Three situations, in particular, can be trust-problematic in the eyes of followers: the triad relationship might (1) make responsibilities blur, (2) create conflicting decisions of human leaders and algorithms, and (3) make employees’ voice unheard. We argue that these situations can undermine employee perceptions of leaders' trustworthiness as followers might start to question a leaders’ ability, benevolence, and integrity if leaders do not understand these novel situations.

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Jan 4th, 12:00 AM Jan 9th, 12:00 AM

The Bermuda Triangle of Leadership in the AI Era? Emerging Trust Implications From “Two-Leader-Situations” in the Eyes of Employees

Online

Artificial Intelligence (AI) and machine learning (ML) algorithms are changing the work in many ways. One hitherto little-studied area is how these technologies are impacting leader-employee relationships, particularly employees’ trust relationships in their “flesh-and-blood” leaders. In this paper, we discuss how algorithms change the nature of leadership when some leadership functions become automated. As a consequence, employees will often find themselves in a “two-leader-situation” with resulting frictions, that create novel leadership focus areas. Three situations, in particular, can be trust-problematic in the eyes of followers: the triad relationship might (1) make responsibilities blur, (2) create conflicting decisions of human leaders and algorithms, and (3) make employees’ voice unheard. We argue that these situations can undermine employee perceptions of leaders' trustworthiness as followers might start to question a leaders’ ability, benevolence, and integrity if leaders do not understand these novel situations.

https://aisel.aisnet.org/hicss-54/os/trust/3