Summary of Let People Fail! Exploring the Influence Of Explainable Virtual and Robotic Agents in Learning-by-doing Tasks, by Marco Matarese et al.
Let people fail! Exploring the influence of explainable virtual and robotic agents in learning-by-doing tasks
by Marco Matarese, Francesco Rea, Katharina J. Rohlfing, Alessandra Sciutti
First submitted to arxiv on: 15 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Human-Computer Interaction (cs.HC); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In this study, researchers investigated how artificial intelligence (AI) agents can influence human behavior during a learning-by-doing task. The team found that when humans interacted with AI agents that provided justifiable explanations for their suggestions, the outcome differed depending on the type of agent involved. Participants who worked with a computer enhanced their task completion times, while those interacting with a humanoid robot were more likely to follow its suggestions without reducing their timing. Interestingly, participants who did not receive assistance from AI achieved better knowledge acquisition than those assisted by explainable AI (XAI). These findings have significant implications for automated tutoring and human-AI collaboration. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Artificial intelligence agents can help people learn new things, but it’s not clear how they affect our behavior. In this study, scientists looked at what happens when humans work with AI agents that can explain why they’re making certain suggestions. They found that the way AI explains its actions depends on the type of agent involved. When people worked with a computer, they finished their tasks faster. With a robot, they were more likely to follow the robot’s advice without doing it any faster. What was surprising is that people who didn’t use AI at all learned better than those who used an AI that could explain its thoughts. |
