# When algorithmic managers fail to fulfill their promises: The role of anthropomorphism in shaping justice perceptions

## TL;DR

This study examines how employees perceive fairness when algorithmic managers fail to keep promises, finding that fairness perceptions depend on promise type and how human-like the manager seems.

## Contribution

The study introduces the moderating role of anthropomorphism in shaping justice perceptions when algorithmic managers fail to fulfill promises.

## Key findings

- Employees perceive lower distributive justice when algorithmic managers fail to fulfill transactional promises, especially when not anthropomorphized.
- Perceived rigidity of algorithmic managers mediates the relationship between promise type and justice perceptions.
- Anthropomorphizing algorithmic managers can reduce negative reactions but raises ethical concerns about accountability.

## Abstract

This study explored how employees perceive distributive justice (i.e., perceived fairness of an outcome) when algorithmic managers fail to fulfill their promises. Moreover, drawing on anthropomorphism theory, we further investigated the moderating role of the anthropomorphism of algorithmic managers. We hypothesized that employees perceive lower distributive justice when their algorithmic manager fails to fulfill transactional rather than relational promises, especially when the manager is not anthropomorphized. We conducted two vignette experiments to test our hypotheses. In both Study 1 (N = 258 employees; Mage = 36.76) and Study 2 (N = 248 employees; Mage = 37.12), a 2 (type of nonfulfilled promises: relational versus transactional) × 2 (algorithmic manager’s anthropomorphism: high versus low) between-subjects design was employed. Study 2 (preregistered) further examined the mediating role of the perceived rigidity of the algorithmic manager in the hypothesized relationships. Study 1 showed that employees perceive lower distributive justice when algorithmic managers fail to fulfill transactional (as opposed to relational) promises, especially when managers are not anthropomorphized. In Study 2, we found that under these conditions, algorithmic managers are perceived as more rigid, which in turn is related to lower perceived distributive justice. These findings highlight the benefits of adding human-like traits to algorithmic management systems to reduce negative reactions when such systems fail to fulfill their commitments. However, ethical concerns arise about encouraging employees to treat algorithmic managers as humans, as anthropomorphization may blur boundaries and undermine accountability.