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Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.8 P.1139-1141

http://doi.org/10.1631/FITEE.2250000


Human-machine augmented intelligence: research and applications


Author(s):  Jianru XUE, Bin HU, Lingxi LI, Junping ZHANG

Affiliation(s):  Institute of Artificial Intelligence and Robotics, Xian Jiaotong University, Xian 710049, China; more

Corresponding email(s):   jrxue@mail.xjtu.edu.cn, bh@lzu.edu.cn, LL7@iupui.edu, jpzhang@fudan.edu.cn

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Jianru XUE, Bin HU, Lingxi LI, Junping ZHANG. Human-machine augmented intelligence: research and applications[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(8): 1139-1141.

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Abstract: 
Current research on artificial intelligence (AI) has been entering a new era, with AI technologies and AI-enabled applications emerging in almost every aspect of human life. Meanwhile, avoiding the risk caused by limitations of AI technologies has become a grand challenge. The main idea of human-machine augmented intelligence (HAI) is to adopt the role of humans or to embed human-like cognitive abilities into intelligent machines. Increasing attention and efforts from academia, industry, and governments are attracted by the HAI idea, whose effects are far-reaching.

Two fundamental formulations of HAI include human-in-the-loop HAI (HITL-HAI) and cognitive computing based HAI (CC-HAI), which have become hot and fundamental frontiers of AI, and an increasing amount of original research has emerged in recent years.

Recent existing research activities on HITL-HAI include theories for human-machine collaboration, human-brain interfaces, human-machine coordination and teaming, and advanced perception and smart environments for human-machine collaboration. In particular, HITL-HAI has been widely used in interactive simulation models in aviation, driving, and robotics. In such simulations, humans play an important role because they influence the simulated environment with their own actions. Brain-computer interfaces have become increasingly important among communication channels for human-machine collaboration.

CC-HAI aims to develop computational models to mimic the mechanism or function of the human brain and improve a machine’s capabilities of perception, reasoning, and decision-making. We have witnessed an increasing amount of research work on casual models, intuitive reasoning models, and associative memories that are proposed with the forms of deep neural networks.

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