Forgiveness is essential for maintaining cooperation and resolving conflicts in social interactions. As artificial agents become more prevalent in interpersonal contexts, human-robot interactions (HRI) are becoming increasingly common. Nowadays, people are confronted with the decision to forgive not only human transgressors, but also robotic ones. To address this emerging social challenge, this research investigates how different post-offense behavioral responses from humans versus robots influence forgiveness, and explores the underlying psychological mechanisms through a dual-path framework that involves cognitive and affective factors. Across two experiments (each with a total sample size of N = 320), participants engaged in scenarios in which either a human or a robot committed an offense and subsequently exhibited one of four behavioral responses: no response, apology, self-deprecating humor, or self-punishment. Both experiments systematically manipulated agent type and behavioral response types.

In Experiment 1, the offense and behavioral response were presented textually. By employing a 2 (agent type: human vs. robot)×4 (behavioral response type: no response vs. apology vs. self-deprecating humor vs. self-punishment) between-subjects design, Experiment 1 revealed significant main effects of both the agent type and behavioral response type on forgiveness. Specifically, participants were more likely to forgive robots than humans. Confirming our mechanistic hypotheses, mediation analyses showed that perceived net benefit and net positive affect significantly mediated the effect of agent type on forgiveness, highlighting the role of cognitive and affective factors in shaping forgiveness.

Experiment 2 partially replicated and extended the findings of Experiment 1 using more ecologically valid video stimuli, which made the behavioral responses of human and robot offenders visible and thus more vivid and realistic. The main effects were validated once again. Mediation analysis revealed that people tend to forgive robots more readily, primarily due to higher levels of perceived net positive affect. Additionally, Experiment 2 revealed a significant interaction effect: the same behavioral response can have different effects on forgiveness depending on whether it is performed by a human or a robot. Specifically, compared to human, robots demonstrated a relative advantage in promoting forgiveness when adopting a self-punishment strategy. Building on this significant interaction, Experiment 2 further explored the psychological mechanisms through which agent type influenced forgiveness under different behavioral responses. Mediation analysis revealed that in the self-punishment condition, both net benefit and net positive affect significantly mediated the effect of agent type on forgiveness. These results suggest that when engaging in self-punishment, robots elicited greater perceptions of net benefit and net positive affect, thereby increasing their likelihood of being forgiven. Additionally, as a supplementary analysis, we conducted computational modeling. The results indicated that agent type and behavioral response type influenced individuals’ aversion to advantageous inequity, rather than altering their underlying decision algorithm in the context of forgiveness-related decisions.

The main novel contribution of this study lies in extending the scope of forgiveness research to include robots, an area that has been largely overlooked before. Most previous studies have focused on forgiveness toward humans, typically explaining it using the dual-path framework of cognition and affect. In response to the growing relevance of artificial intelligence in contemporary society, the present study examines forgiveness toward robots. The findings provide preliminary support for the applicability of the cognition-affect dual-process framework in explaining forgiveness toward robots, thereby extending its theoretical scope to encompass human-robot interactions.

In conclusion, this study revealed two key findings. First, in the context of social offenses, individuals exhibited greater forgiveness toward robots than toward humans - a pattern primarily mediated by perceived net positive affect, with perceived net benefit also potentially contributing. Second, robots demonstrated a relative advantage over humans in eliciting forgiveness when using a self-punishment strategy.