A Survey of Hybrid Human-Artificial Intelligence for Social Computing
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Abstract (arXiv)
Along with the development of modern computing technology and social sciences, both theoretical research and practical applications of social computing have been continuously extended. In particular with the boom of artificial intelligence (AI), social computing is significantly influenced by AI. However, the conventional technologies of AI have drawbacks in dealing with more complicated and dynamic problems. Such deficiency can be rectified by hybrid human-artificial intelligence (H-AI) which integrates both human intelligence and AI into one unity, forming a new enhanced intelligence. H-AI in dealing with social problems shows the advantages that AI can not surpass. This paper firstly introduces the concept of H-AI. AI is the intelligence in the transition stage of H-AI, so the latest research progresses of AI in social computing are reviewed. Secondly, it summarizes typical challenges faced by AI in social computing, and makes it possible to introduce H-AI to solve these challenges. Finally, the paper proposes a holistic framework of social computing combining with H-AI, which consists of four layers: object layer, base layer, analysis layer, and application layer. It represents H-AI has significant advantages over AI in solving social problems.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 0 of its 47 references that are in the map. First posted on arXiv 17 Mar 2021.
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Citing papers per year: 2022: 2; 2023: 2; 2024: 0; 2025: 0; 2026: 1.
5 papers.
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- 2026MoCA: Implicit Social Context Analysis6 Aug 2026
- 2023Context-Aware Service Recommendation System for the Social Internet of Things14 Aug 2023
- 2023Task Offloading for Smart Glasses in Healthcare: Enhancing Detection of Elevated Body Temperature14 Aug 2023
- 2022Edge-enabled Metaverse: The Convergence of Metaverse and Mobile Edge Computing13 Apr 2022
- 2022Artificial Intelligence for Suicide Assessment using Audiovisual Cues: A Review22 Jan 2022