4.6 Review

Mind Meets Machine: Towards a Cognitive Science of Human-Machine Interactions

期刊

TRENDS IN COGNITIVE SCIENCES
卷 25, 期 3, 页码 200-212

出版社

CELL PRESS
DOI: 10.1016/j.tics.2020.11.009

关键词

-

资金

  1. European Research Council under the European Union [677270]
  2. Leverhulme Trust [PLP-2018-152]
  3. Macquarie University (MQRIS: Building Social Robotics Capacity Across Disciplines and Departments)
  4. European Research Council (ERC) [677270] Funding Source: European Research Council (ERC)

向作者/读者索取更多资源

As robots move from the realm of science fiction to real-life settings, understanding the mechanisms behind human-machine interactions becomes increasingly crucial. A framework has been introduced to study the cognitive and brain mechanisms supporting these interactions, linking different levels of description with relevant theory and methods. It presents a challenging yet rewarding opportunity for brain and behavioral scientists to explore the diverse nature of social machines and individuals' experiences, respecting the diversity of cognitive and brain systems.
As robots advance from the pages and screens of science fiction into our homes, hospitals, and schools, they are poised to take on increasingly social roles. Consequently, the need to understand the mechanisms supporting human-machine interactions is becoming increasingly pressing. We introduce a framework for studying the cognitive and brain mechanisms that support human-machine interactions, leveraging advances made in cognitive neuroscience to link different levels of description with relevant theory and methods. We highlight unique features that make this endeavour particularly challenging (and rewarding) for brain and behavioural scientists. Overall, the framework offers a way to study the cognitive science of human-machine interactions that respects the diversity of social machines, individuals' expectations and experiences, and the structure and function of multiple cognitive and brain systems.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据