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Koch, J., & Oulasvirta, A. (2018). Group cognition and collaborative ai. In Human and Machine Learning (pp. 293–312).Springer. 
Added by: SijanLibrarian (2020-09-24 10:48:18)   Last edited by: SijanLibrarian (2020-09-24 10:50:27)
Resource type: Book Article
BibTeX citation key: Koch2018
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Categories: Artificial Intelligence, Cognitive Science, Complexity Science, Computer Science, Decision Theory, Engineering, General, Military Science, Sociology
Subcategories: Augmented cognition, Decision making, Human decisionmaking, Human factors engineering, JADC2, Machine learning, Networked forces, Psychology of human-AI interaction, Social cognition, Social networks, Systems theory
Creators: Koch, Oulasvirta
Publisher: Springer
Collection: Human and Machine Learning
Views: 48/62
Views index: 16%
Popularity index: 4%
Abstract
Significant advances in artificial intelligence suggest that we will be using intelligent agents on a regular basis in the near future. This chapter discusses group cognition as a principle for designing collaborative AI. Group cognition is the ability to relate to other group members’ decisions, abilities, and beliefs. It thereby allows participants to adapt their understanding and actions to reach common objectives. Hence, it underpins collaboration. We review two concepts in the context of group cognition that could inform the development of AI and automation in pursuit of natural collaboration with humans: conversational grounding and theory of mind. These concepts are somewhat different from those already discussed in AI research. We outline some new implications for collaborative AI, aimed at extending skills and solution spaces and at improving joint cognitive and creative capacity.
  
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