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ACM Transactions on Interactive Intelligent Systems (TiiS) Special Issue on Trust and Influence in Intelligent Human-Machine Interaction

机译:ACM交互式智能系统(TiiS)交易有关智能人机交互中的信任和影响的特刊

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Recent advances in machine intelligence and robotics have enabled new forms of human-computer interaction characterized by greater adaptability, shared decision-making, and mixed initiative. These advances are leading toward machines that can operate with relative autonomy but are designed to interact or engage with human counterparts in joint human-machine teams. The degree to which people trust machines is critical to the efficacy of these teams. People will cooperate with, and rely upon, intelligent agents they trust. Those they do not trust fall into disuse. As intelligent agents become more self-directed, learn from their experiences, and adapt behavior over time, the relationship between people and machines becomes more complex, and designing system behaviors to engender the proper level of trust becomes more challenging. Moreover, as intelligent systems become common in safety-critical domains, we must understand and assess the influence they might exert on human decision making to avoid unintended consequences, such as over-trust, compliance, or undue influence. Online social environments further complicate human-machine relationships. In the social media ecosystem, intelligent agents (e.g., chatbots) might act as aids or assistants but also as competitors or adversaries. In this context, research challenges include understanding how human-machine relationships evolve in social media and especially how humans develop trust and are susceptible to influence in social networks.
机译:机器智能和机器人技术的最新进展已实现了新形式的人机交互,其特点是适应性强,决策共享性和主动性强。这些进步导致机器可以相对自治地运行,但旨在与联合的人机团队中的人进行交互或参与。人们对机器的信任程度对于这些团队的效率至关重要。人们将与他们信任的智能代理合作并依靠它们。他们不信任的人将被废弃。随着智能代理变得更加自我指导,从他们的经验中学习以及随着时间的推移适应行为,人与机器之间的关系变得更加复杂,设计系统行为以实现适当的信任水平也变得更具挑战性。此外,随着智能系统在对安全至关重要的领域中变得越来越普遍,我们必须了解并评估它们可能对人为决策产生的影响,以避免意外后果,例如过度信任,合规或不当影响。在线社交环境进一步使人机关系复杂化。在社交媒体生态系统中,智能代理(例如,聊天机器人)可以充当辅助工具或助手,也可以充当竞争对手或对手。在这种情况下,研究挑战包括了解人机关系如何在社交媒体中发展,尤其是人类如何建立信任并易受社交网络影响。

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