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<p>The growing presence of Socially Interactive Agents (SIAs) in educational, professional, and domestic contexts raises questions about their role in reflecting and shaping social biases. This overview summarises and critically reflects on a series of studies that were conducted on bias and diversity in interactions with SIAs. Building on theories of social identity, linguistic bias, and intersectionality, we explore how users perceive and evaluate SIAs based on social cues such as language, accent, ethnicity, and gender. Our findings suggest that established psychological mechanisms, such as in-group favouritism, stereotyping, and categorisation also apply to human-agent interaction. Beyond diagnosis, the paper discusses how SIAs might be used to challenge and reduce bias, drawing on approaches such as intergroup contact, and counter-stereotypical design. At the same time, we critically question the ethical implications of simulating marginalised identities in virtual environments and address risks. We conclude by outlining future research directions aimed at designing culturally sensitive and socially responsible agents that not only reflect human diversity but actively support fairness and inclusion.</p>

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Researching diversity and bias using socially interactive agents: an overview

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月4日

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  • Ohenewa Bediako Akuffo,
  • Juliette Claßen,
  • Birgit Lugrin

摘要

The growing presence of Socially Interactive Agents (SIAs) in educational, professional, and domestic contexts raises questions about their role in reflecting and shaping social biases. This overview summarises and critically reflects on a series of studies that were conducted on bias and diversity in interactions with SIAs. Building on theories of social identity, linguistic bias, and intersectionality, we explore how users perceive and evaluate SIAs based on social cues such as language, accent, ethnicity, and gender. Our findings suggest that established psychological mechanisms, such as in-group favouritism, stereotyping, and categorisation also apply to human-agent interaction. Beyond diagnosis, the paper discusses how SIAs might be used to challenge and reduce bias, drawing on approaches such as intergroup contact, and counter-stereotypical design. At the same time, we critically question the ethical implications of simulating marginalised identities in virtual environments and address risks. We conclude by outlining future research directions aimed at designing culturally sensitive and socially responsible agents that not only reflect human diversity but actively support fairness and inclusion.