Exploring Automated Leadership and Agent Interaction Modalities

Abstract

Advances in computer technology and research in the field of artificial intelligence have enabled computers to take on roles traditionally held by humans. Insights from leadership research have identified behaviors that, when applied strategically and systematically, can improve individual and team performance. We propose that some aspects of leadership are candidates for automation. This paper briefly reviews relevant leadership literature and describes three leadership behaviors that may be possibly automated: goal setting, performance monitoring, and performance consequences. The paper also explores the relationship of different embodiments of the artificial leaders, the impact of these embodiments in conveying social presence and the impact of this presence on performance and satisfaction outcomes. We conducted an experiment to investigate the effect of automated leadership on follower attitudes and behavior. Initial results suggest that automated leadership may positively influence performance and accuracy for individuals engaged in a clerical task.

Human–Algorithm Collaboration Works Best if Humans Lead (Because it is Fair!)

“…In other words, the business model that seems to be emerging and is put in practice in today's business world is that algorithms will lead increasingly more the management of (routine) decisions and execution of jobs in its different aspects. As a result, human employees will become more regularly followers at certain times when automation sets in , 2020aDerrick & Elson, 2019). In fact, some organizations are already deploying what is known as algorithmic management (Duggan et al, 2020).…”

“…The existence of a tension between the emerging business model that algorithms will move into leading human jobs within organizations on one hand, and observations that those algorithms taking over the leadership of jobs are opposed by the human workforce on the other hand, represents a challenge to organizations that is (a) not understood well and ( b) not yet analyzed in terms of how the reality of autonomous algorithms can be optimally used in collaboration with a human workforce. Given the market demand for business efficiency, it is inevitable that algorithms are and will be replacing various jobs at different levels of managerial discretion and as such seem destined to take over leadership from humans in many ways (Derrick & Elson, 2019;Dewhurst, & Willmot, 2014;Parry et al, 2016). As Pasquale noted, "authority is increasingly expressed algorithmically" (2015: p. 8; see also Lindebaum et al, 2020).…”

Vero: A Method for Remotely Studying Human-AI Collaboration

“…In the human-AI collaboration literature, some of the most pressing open questions involve user perceptions of AI humanness, capabilities, and transparency [7,4,3]. Researchers within IS have started to investigate such questions, with recent work examining topics ranging from symbiotic co-evolution of human-AI teams [8], trust of intelligent systems [9,10] and interaction design [11,6,12,13] to developing scales for measuring perceived AI intelligence and anthropomorphism [5].…”

LeadLets: Towards a Pattern Language for Leadership Development of Human and AI Agents

“…The role of AI is rapidly advancing from being reactive support providers to being interactive teammates that work hand in hand with teams to facilitate high quality outcomes [47]. We already have AI systems that act as companion robots to provide company to the elderly [45], decision making systems that help us navigate through complex problems [32], and warning systems that protect us in face of danger whether it is on the road [48], severe weather [8], or human deception [26,27]. However, to our knowledge, research and development has not reached a point where AI is capable of critical thinking and problem solving at par with human abilities.…”

“…As noted above, the first step towards developing leadership AI is to code the leadership process into observable behaviors that move one or more followers towards achieving the leader's goal [26]. Importantly, these coded behaviors must be reusable, predictable, and easily transferable for them to be useful as a foundation for both novice humans and AI algorithms [14].…”