Artificial intelligence advances have led to robots endowed with increasingly sophisticated social abilities. These machines speak to our innate desire to perceive social cues in the environment, as well as the promise of robots enhancing our daily lives. However, a strong mismatch still exists between our expectations and the reality of social robots. We argue that careful delineation of the neurocognitive mechanisms supporting human-robot interaction will enable us to gather insights critical for optimising social encounters between humans and robots. To achieve this, the field must incorporate human neuroscience tools including mobile neuroimaging to explore long-term, embodied human-robot interaction in situ. New analytical neuroimaging approaches will enable characterisation of social cognition representations on a finer scale using sensitive and appropriate categorical comparisons (human, animal, tool, or object). The future of social robotics is undeniably exciting, and insights from human neuroscience research will bring us closer to interacting and collaborating with socially sophisticated robots.

中文翻译：

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人机交互时代的社会认知

人工智能的进步使机器人具有越来越复杂的社交能力。这些机器表达了我们对感知环境中社会线索的与生俱来的渴望，以及机器人改善我们日常生活的承诺。然而，我们的期望与社交机器人的现实之间仍然存在严重的不匹配。我们认为，仔细描绘支持人机交互的神经认知机制将使我们能够收集对优化人类与机器人之间的社交接触至关重要的见解。为了实现这一目标，该领域必须结合包括移动神经成像在内的人类神经科学工具，以探索长期、具身的人机交互原位。新的分析神经成像方法将能够使用敏感和适当的分类比较（人类、动物、工具或物体）在更精细的尺度上表征社会认知表征。不可否认，社交机器人的未来令人兴奋，来自人类神经科学研究的见解将使我们更接近于与复杂的社交机器人进行交互和协作。