@article{Shi2023, 
author = {Feifei Shi and Fang Zhou and Hong Liu and Liming Chen and Huansheng Ning},
title = {Survey and Tutorial on Hybrid Human-Artificial Intelligence},
year = {2023},
journal = {Tsinghua Science and Technology},
volume = {28},
number = {3},
pages = {486-499},
keywords = {Internet of Things (IoT), artificial intelligence (AI), hybrid human-artificial intelligence (H-AI)},
url = {https://www.sciopen.com/article/10.26599/TST.2022.9010022},
doi = {10.26599/TST.2022.9010022},
abstract = {The growing computing power, easy acquisition of large-scale data, and constantly improved algorithms have led to a new wave of artificial intelligence (AI) applications, which change the ways we live, manufacture, and do business. Along with this development, a rising concern is the relationship between AI and human intelligence, namely, whether AI systems may one day overtake, manipulate, or replace humans. In this paper, we introduce a novel concept named hybrid human-artificial intelligence (H-AI), which fuses human abilities and AI capabilities into a unified entity. It presents a challenging yet promising research direction that prompts secure and trusted AI innovations while keeping humans in the loop for effective control. We scientifically define the concept of H-AI and propose an evolution road map for the development of AI toward H-AI. We then examine the key underpinning techniques of H-AI, such as user profile modeling, cognitive computing, and human-in-the-loop machine learning. Afterward, we discuss H-AI’s potential applications in the area of smart homes, intelligent medicine, smart transportation, and smart manufacturing. Finally, we conduct a critical analysis of current challenges and open gaps in H-AI, upon which we elaborate on future research issues and directions.}
}