Adherence to Unethical Instructions from AI Supervisors: Combining Experiments with Machine Learning

Lanz, Lukas; Briker, Roman; Gerpott, Fabiola H.

doi:10.5465/ambpp.2022.12392abstract

Cited by 2 publications

(3 citation statements)

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“…While delegation to AI can improve managerial perceptions of decision quality (Keding & Meissner, 2021), emerging research suggests that employees may have different views and responses to humans or AIs undertaking leadership functions (de Cremer, 2020). For instance, Lanz et al (2023) note that employees are less likely to comply with unethical instructions from an AI than a human supervisor. Future work could examine how those individual‐level beliefs, of leaders, employees, and stakeholders, shape the use and acceptance of AI for certain leadership activities and ultimately impact leader–employee influence processes.…”

Section: Future Research Directions: Opportunities and Challengesmentioning

confidence: 99%

A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice

et al. 2023

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SummaryThe rising use of artificially intelligent (AI) technologies, including generative AI tools, in organizations is undeniable. As these systems become increasingly integrated into organizational practices and processes, understanding their impact on workers' experiences and job designs is critical. However, the ongoing discourse surrounding AI use in the workplace remains divided. Proponents of the technology extol its benefits for enhancing efficiency and productivity, while others voice concerns about the potential harm to human workers. To provide greater clarity on this pressing issue, this article presents a systematic review of empirical research that sheds light on the implications of AI use at work. Organized under five inductively generated themes within a multilevel framework, we uncover individual, group, and organizational factors that shape the interplay between humans and AI. Specifically, the themes are: (1) human–AI collaboration; (2) perceptions of algorithmic and human capabilities; (3) worker attitudes towards AI; (4) AI as a control mechanism in algorithmic management of platform‐based work; and (5) labor market implications of AI use. Our review offers insights into these themes and identifies five pathways for future research. Finally, we provide practical recommendations for organizational leaders seeking to implement AI technologies while prioritizing their employees' well‐being.

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Section: Future Research Directions: Opportunities and Challengesmentioning

confidence: 99%

A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice

et al. 2023

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show abstract

“…Relatedly, third, while initial evidence indicates that humans are less likely to follow the unethical instructions of an AI (versus human) leader (Lanz et al, 2023), at the same time humans seem to experience less moral outrage over algorithmic discrimination than over human discrimination (Bigmann et al, 2022). Accordingly, it contains a risk that decisions of AI leaders that one “has to follow” are used as an excuse for unethical behavior with implications for the potential weakening of collective action to address systematic discrimination and other societal issues (Bigmann et al, 2022).…”

Section: Implications For Leadership Researchmentioning

confidence: 99%

“…In this way, we can hopefully maintain a “human-in-the-loop” pattern (Grønsund & Aanestad, 2020) whereby human leaders still (co-)generate a ground truth against which to assess algorithmic leadership and potentially adapt the underlying AI. Students need to develop a digital backbone in order to stand their ground; against the technology itself when it provides ethically questionable advice (e.g., firing certain employee groups because they underperform, Lanz et al, 2023); against engineers who only see the opportunities of the machine (Köbis et al, 2021); and against a multitude of consultants who want to integrate ever new technologies without considering their broader impact.…”

Section: Implications For Leadership Educationmentioning

confidence: 99%

The Now, New, and Next of Digital Leadership: How Artificial Intelligence (AI) Will Take Over and Change Leadership as We Know It

Quaquebeke

Gerpott

2023

Journal of Leadership & Organizational Studies

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There is an emerging consensus that traditional management roles could—and maybe should—be performed by machines infused with Artificial Intelligence (AI). Yet, “true” leadership—that is, motivating and enabling people so that they can and will contribute to the collective goals of an organization—is still predominantly viewed as the prerogative of humans. With our opinion piece, we challenge this perspective. Our essay aims to be a wake-up call for large parts of academia and practice that romanticize human leadership and think that this bastion can never be overtaken by AI. We delineate why algorithms will not (need to) come to a halt before core characteristics of leadership and potentially cater better to employees’ psychological needs than human leaders. Against this background, conscious choices need to be made about what role humans are to play in the future of leadership. These considerations hold significant implications for the future of not only leadership research but also leadership education and development.

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Adherence to Unethical Instructions from AI Supervisors: Combining Experiments with Machine Learning

Cited by 2 publications

References 0 publications

A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice

A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice

The Now, New, and Next of Digital Leadership: How Artificial Intelligence (AI) Will Take Over and Change Leadership as We Know It

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