From Algorithmic Decisions to Human Trust: A Narrative Review of Organizational Communication in AI-Mediated Workplaces

Abstract

In the past, human managers were responsible for making various workplace decisions-now, this responsibility is often shared with artificial intelligence (AI) making decisions. This new shared responsibility also creates new complexities in the context of human-to-human and human-to-organization relationships. This paper is a narrative review examining how AI decisions in the workplace contribute to human-human (employee-to-employee and employee-to-manager) and organization-human (organization-to-employee) communication, and under what communication conditions employee trust in their organization may emerge. Six interconnected themes were identified across the literature: algorithmic opacity and communication gaps; transparency and explainability; organizational justice and perceived fairness; employee voice, contestability, and human agency; human-AI-manager communication and human oversight; and trust as an organizational outcome. This review contributes a synthesized framework linking organizational communication practices, including transparency, explainability, employee voice, human oversight, accountability, and perceived fairness, to trust outcomes in AI-mediated workplaces. Findings from the various fields included in this review indicate that, for human beings to extend their trust to decisions made utilizing an AI, it is necessary not only for the algorithm’s judgments to be accurate, but for those decisions to be understandable, contestable and to have clearly demarcated humans accountable. Based upon the findings from this research and the themes identified herein, a Human-centered Communication framework was developed linking human transparency and explainability; employee voice; human rather than purely automated management; human-system accountability; perceived fairness and trust in the organization.