A Survey of Hybrid Human-Artificial Intelligence for Social Computing

Wenxi Wang, Huansheng Ning, Feifei Shi, Sahraoui Dhelim, Weishan Zhang, Luke Chen

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Abstract

With the convergence of modern computing technology and social sciences, both theoretical research and practical applications of social computing have been extended to new domains. In particular, social computing was significantly influenced by the recent advances of artificial intelligence (AI). However, the conventional technologies of AI have various drawbacks in dealing with 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 some advantages over the conventional AI. This article firstly reviews the latest research progresses of AI in social computing. Secondly, it summarizes typical challenges AI faces in social computing, which motivate the necessity to introduce H-AI to tackle social-oriented problems. Finally, we discuss the concept of H-AI and propose a holistic architecture of H-AI in social computing, which consists of three layers: object layer, intelligent processing layer, and application layer. The proposed architecture shows that H-AI has significant advantages over AI in solving social problems.
Original languageEnglish
JournalIEEE Transactions on Human-Machine Systems
Early online date21 Dec 2021
DOIs
Publication statusE-pub ahead of print - 21 Dec 2021

Bibliographical note

Publisher Copyright:
IEEE

Keywords

  • Affective computing
  • Artificial intelligence
  • Artificial intelligence (AI)
  • Human intelligence
  • Neural networks
  • Particle swarm optimization
  • Social computing
  • Social networking (online)
  • hybrid human-artificial intelligence (H-AI)
  • social computing

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