Empathy and Schadenfreude in Human-Robot Teams

Area of Science:

• Social Psychology
• Human-Robot Interaction
• Cognitive Science

Background:

• Intergroup dynamics significantly influence social interactions, leading to biases such as empathy towards ingroup members and schadenfreude (pleasure from outgroup misfortune).
• Understanding if these biases extend to interactions with non-human agents like robots is crucial for the future of human-robot collaboration.

Purpose of the Study:

• To investigate the presence and extent of intergroup biases (empathy and schadenfreude) in human-robot interactions.
• To compare these biases in human-human versus human-robot teams.
• To examine the influence of robot's human likeness and team identification on these biases.

Main Methods:

• Four experiments involving 361 participants assessed emotional reactivity during a competitive reaction time game.
• Empathy and schadenfreude were measured by analyzing participants' responses to ingroup and outgroup team members' outcomes.
• Robot's human likeness was varied (humanoid vs. mechanoid), and team identification levels were recorded.

Main Results:

• A consistent intergroup bias was observed, with participants showing more empathy towards ingroup members and more schadenfreude towards outgroup members.
• These biases were present regardless of whether the team member was human or robot, with no significant difference in reported empathy or schadenfreude.
• The human likeness of the robot did not consistently affect the intergroup bias.
• Higher levels of team identification correlated with stronger intergroup empathy and schadenfreude biases.

Conclusions:

• Intergroup biases observed in human-human interactions are replicated in human-robot interactions, indicating a fundamental aspect of social cognition.
• The nature of the agent (human vs. robot) does not eliminate these biases, suggesting that team membership is a primary driver.
• Team identification plays a significant role in modulating these biases, highlighting its importance in social dynamics involving robots.