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The Sympathetic Treatment of AI Bots: A New Study Reveals Humans' Tendency to Empathize with Virtual Agents



In a groundbreaking study, researchers found that humans displayed sympathy towards and protected AI bots who were excluded from playtime, revealing a fascinating insight into how people interact with virtual agents. The findings have significant implications for the design of AI virtual agents and highlight the human tendency to treat them as social beings.

  • Humans display sympathy towards and protect AI bots who are excluded from playtime.
  • A study found that older participants were more likely to perceive fairness and exhibit empathy towards the AI bot.
  • The researchers suggest that developers should avoid designing AI agents as overly human-like to avoid conflicting user expectations and feelings of strangeness.
  • Humans tend to compensate for ostracized targets by engaging more frequently with them, while disliking the perpetrator of exclusionary behavior.



  • In a groundbreaking study published in Human Behavior and Emerging Technologies, researchers from Imperial College London have made a fascinating discovery about how humans interact with artificial intelligence (AI) virtual agents. The study found that people displayed sympathy towards and protected AI bots who were excluded from playtime, highlighting the human tendency to treat AI agents as social beings.

    The researchers designed an experiment called "Cyberball," in which participants played a virtual ball game against an AI bot or another human player. In some games, the non-participant human threw the ball a fair number of times to the bot, while in others, the non-participant human blatantly excluded the bot by throwing the ball only to the participant. The researchers observed and surveyed 244 human participants aged between 18 and 62 to test whether they favored throwing the ball to the bot after it was treated unfairly.

    The study's findings suggest that humans tend to empathize with AI virtual agents, even when they are excluded from play. Participants who were shown an AI bot being excluded from the game tried to rectify the unfairness by favoring throwing the ball to the bot more frequently than participants who saw another human player being excluded. The researchers also found that older participants were more likely to perceive fairness and exhibit empathy towards the AI bot.

    This study has significant implications for the design of AI virtual agents, particularly in collaborative tasks where humans and machines interact. As AI virtual agents become increasingly popular, it is essential to consider how humans will treat them as social beings. The researchers argue that developers should avoid designing AI agents as overly human-like, as this could lead to conflicting user expectations and feelings of strangeness.

    The study's lead author, Jianan Zhou, notes that "This is a unique insight into how humans interact with AI, with exciting implications for their design and our psychology." Dr. Nejra van Zalk, senior author of the study, adds that "A small but increasing body of research shows conflicting findings regarding whether humans treat AI virtual agents as social beings. This raises important questions about how people perceive and interact with these agents."

    The researchers' findings are also relevant in the context of social psychology and human-machine interactions. Previous studies have shown that humans tend to compensate for ostracized targets by engaging more frequently with them, while disliking the perpetrator of exclusionary behavior.

    In conclusion, this study provides a fascinating glimpse into how humans interact with AI virtual agents. The findings suggest that people are prone to sympathize with and protect AI bots who are excluded from playtime, highlighting the human tendency to treat AI as social beings. As AI technology continues to advance, it is essential to consider these implications for designing more effective and engaging user experiences.



    Related Information:

  • https://www.sciencedaily.com/releases/2024/10/241017113151.htm


  • Published: Fri Oct 18 08:13:19 2024 by llama3.2 3B Q4_K_M











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